Implantable systems and methods for identifying a contra-ictal condition in a subject

ABSTRACT

Systems and methods of monitoring a subject&#39;s neurological condition are provided. In some embodiments, the method includes the steps of analyzing a physiological signal (such as an EEG) from a subject to determine if the subject is in a contra-ictal condition; and if the subject is in a contra-ictal condition, providing an indication (e.g., to the subject and/or to a caregiver) that the subject is in the contra-ictal condition. The systems and methods may utilize a minimally invasive, leadless device to monitor the subject&#39;s condition. In some embodiments, if the subject is in a pro-ictal condition, the method includes the step of providing an indication (such as a red light) that the subject is in the pro-ictal condition.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.12/053,312, filed Mar. 21, 2008 now U.S. Pat. No. 8,036,736 whichapplication claims the benefit of priority to U.S. Provisional PatentApplication No. 60/919,364, filed Mar. 21, 2007, the disclosures ofwhich are incorporated by reference herein in their entirety.

BACKGROUND OF THE INVENTION

The present invention relates generally to systems and methods formonitoring a subject's neurological condition. More specifically, thepresent invention is related to minimally invasive methods and systemsfor monitoring a subject who has epilepsy and determining if the subjectis in a contra-ictal condition in which the subject is at lowsusceptibility for a seizure and is unlikely to transition into apre-seizure condition within a computed or predetermined time period.

Epilepsy is a disorder of the brain characterized by chronic, recurringseizures. Seizures are a result of uncontrolled discharges of electricalactivity in the brain. A seizure typically manifests itself as sudden,involuntary, disruptive, and often destructive sensory, motor, andcognitive phenomena. Seizures are frequently associated with physicalharm to the body (e.g., tongue biting, limb breakage, and burns), acomplete loss of consciousness, and incontinence. A typical seizure, forexample, might begin as spontaneous shaking of an arm or leg andprogress over seconds or minutes to rhythmic movement of the entirebody, loss of consciousness, and voiding of urine or stool.

A single seizure most often does not cause significant morbidity ormortality, but severe or recurring seizures (epilepsy) results in majormedical, social, and economic consequences. Epilepsy is most oftendiagnosed in children and young adults, making the long-term medical andsocietal burden severe for this population of subjects. People withuncontrolled epilepsy are often significantly limited in their abilityto work in many industries. An uncommon, but potentially lethal form ofseizure is called status epilepticus, in which a seizure continues formore than 30 minutes. This continuous seizure activity may lead topermanent brain damage, and can be lethal if untreated.

While the exact cause of epilepsy is often uncertain, epilepsy canresult from head trauma (such as from a car accident or a fall),infection (such as meningitis), or from neoplastic, vascular, ordevelopmental abnormalities of the brain. Most epilepsy, especially mostforms that are resistant to treatment (i.e., refractory), are idiopathicor of unknown causes, and are generally presumed to be an inheritedgenetic disorder. Demographic studies have estimated the prevalence ofepilepsy at approximately 1% of the population, or roughly 2.5 millionindividuals in the United States alone. Approximately 60% of thesesubjects have focal epilepsy where a defined point of onset can beidentified in the brain and are therefore candidates for some form of afocal treatment approach.

If it is assumed that an “average” subject with focal epilepsy hasbetween 3 and 4 seizures per month, in which each of the seizures lastfor several seconds or minutes, the cumulative time the subject would beseizing is only about one hour per year. The other 99.98% of the year,the epileptic subject is free from seizures. The debilitating aspect ofepilepsy is the constant uncertainty of when the next seizure is goingto strike. It is this constant state of uncertainty which causesepileptic subjects to remove themselves from society. It is the constantfear and uncertainty of when the next seizure will strike that preventsthe person from performing activities that most non-epileptic subjectstake for granted.

To that end, there have been a number of proposals from groups aroundthe world for predicting seizures and warning the subject of theimpending seizure. Most of such proposals attempt to analyze thesubject's electroencephalogram or electrocorticograms (referred tocollectively as “EEGs”), to differentiate between a “pre-ictalcondition” (i.e., pre-seizure condition) and an “inter-ictal condition”(i.e., between seizures). To date, however, none of the proposed systemshave proven to be effective in predicting seizures. Some researchershave proposed that seizures develop minutes to hours before the clinicalonset of the seizure. These researchers therefore classify the pre-ictalcondition as the beginning of the ictal or seizure event which beginswith a cascade of events. Under this definition, a seizure is imminentand will occur if a pre-ictal condition is observed. Others believe thata pre-ictal condition represents a state which only has a highsusceptibility for a seizure and does not always lead to a seizure, andthat seizures occur either due to chance (e.g., noise) or via atriggering event during this high susceptibility time period. Forclarity, the term “pro-ictal” is introduced here to represent a state orcondition that represents a high susceptibility for seizure; in otherwords, a seizure can happen at any time. Ictal activity, within thescope of epilepsy, refers to seizure activity. Ictal activity may haveother meanings in other contexts.

SUMMARY OF THE INVENTION

Prior art seizure detection and warning systems focused only on theidentification of ictal or pro-ictal physiological data from thesubject. See, e.g., Litt U.S. Pat. No. 6,658,287. While being able todetermine that the subject is in a “pro-ictal” condition is highlydesirable, identifying when the subject has entered or is likely toenter a pro-ictal condition is only part of the solution for thesesubjects. An equally important aspect of any seizure advisory system isthe ability to be able to inform the subject when they are unlikely tohave a seizure for a predetermined period of time (e.g., lowsusceptibility or “contra-ictal”). Simply knowing that the subject isnot pro-ictal does not provide the subject with the assurance that theywill not quickly transition into a pro-ictal or ictal condition. Knowingthat they are in a contra-ictal state can allow the subject to engage innormal daily activities, such as walking down a set of stairs, withoutfearing that they will have a seizure. Knowing when a seizure isunlikely to occur can be even more important for the subject's sense offreedom than being alerted when a seizure is likely to occur.

Furthermore, for one reason or another, it may not be possible toaccurately predict the seizures in a portion of the subject population.However, for that same portion of the subject population, it may bepossible to let the subject know when they are unlikely to have aseizure for a period of time.

Accordingly, it would be desirable to provide methods and systems thatare able to inform the subject that they are highly unlikely totransition into a pro-ictal or ictal condition in a period of time. Itwould further be desirable if such systems and methods couldsubstantially continuously provide an output to the subject in aminimally invasive fashion to differentiate when the subject is at a lowsusceptibility to seizure, raised susceptibility to seizure, and/or ahigh susceptibility to seizure.

Systems and methods are described herein for identifying a state orcondition in which the subject is unlikely to transition to an ictalstate or condition within a time period. Such a state is describedherein as a “contra-ictal” condition or state. If it is determined thatthe subject is in the contra-ictal state, a communication is output tothe subject that is indicative of the subject being in the contra-ictalstate.

In some embodiments, the present invention may provide a substantiallycontinuous output to the subject that indicates the subject's real-timesusceptibility to a seizure for a time period. The output may provide anindication that the subject is at a high susceptibility to a seizure(e.g., seizure prediction or determination of being in a pre-ictalcondition), a mild or normal susceptibility to a seizure (e.g., thesubject is in an inter-ictal state), or a low susceptibility to aseizure (e.g., the subject appears to be highly unlikely to have aseizure within a time period).

The term “state” is used herein to generally refer to calculationresults or indices that are reflective of the state of the subject'sneural system, but does not necessarily constitute a complete orcomprehensive accounting of the subject's total neurological condition.The estimation and characterization of “state” may be based on one ormore subject dependent parameters from the brain, such as electricalsignals from the brain, including but not limited toelectroencephalogram signals “EEG” and electrocorticogram signals “ECoG”(referred to herein collectively as “EEG”), brain temperature, bloodflow in the brain, concentration of anti-epileptic drugs (AEDs) in thebrain, or other physiological signals.

The term “pro-ictal” is used herein to refer to a neurological state orcondition characterized by an increased likelihood of transition to anictal state. A pro-ictal state may transition to either an ictal orinter-ictal state. A pro-ictal state that transitions to an ictal stateis also referred to as pre-ictal.

Minimally-invasive systems that provide for the long-term, ambulatorymonitoring of subject's brain activity are described. These systems willtypically include one or more implantable devices that may be minimallyinvasively implanted in the subject. The implantable device may beadapted to sample a physiological signal from a subject. A processingassembly processes a data signal from the implantable device todetermine if the subject is in a contra-ictal condition. If the subjectis determined to be in a contra-ictal condition, a user interfaceprovides an output to the subject that indicates that the subject is inthe contra-ictal condition.

The data signal can be indicative of the physiological signal and can besubstantially continuously transmitted substantially in real-time fromthe implanted minimally invasive leadless device to the processingassembly. The data signal can comprise a compressed EEG signal or anencrypted EEG signal, or it may comprise an extracted feature from aphysiological signal from the subject. The user interface can provide asubstantially continuous output to the subject regarding the subject'scondition.

The minimally invasive leadless device can be in wireless communicationwith the processing assembly. The processing assembly and the userinterface can both be part of a patient handheld device.

The contra-ictal condition can include a condition in which the subjectis at a low susceptibility to having a seizure within a time period.

The output to the subject that indicates that the subject is in thecontra-ictal condition can comprise an audible output, a tactile output,a visual output on a display, or a combination thereof. The output tothe subject can comprise, e.g., a green light.

In another embodiment, a seizure advisory system is provided comprisingan implanted leadless device that is configured to sample an EEG signal(or other physiological signal) from a subject and transmit a wirelesssignal from the subject's body to a subject advisory device that isexternal to the subject's body. The subject advisory device comprises aprocessing assembly that processes the wireless signal to determine ifthe subject is in a contra-ictal condition. If the user is determined tobe in a contra-ictal condition, a user interface of the subject advisorydevice provides an output to the subject that indicates that the subjectis in the contra-ictal condition.

The subject advisory device can comprise a memory for storing thewireless signal. The contra-ictal condition can be a neurological statein which the subject is unlikely to transition into an ictal conditionwithin a time period. The time period can be a predetermined timeperiod.

The leadless device can be adapted to be implanted between the subject'sdura and scalp, and preferably between the subject's skull and scalp.

In yet another embodiment, a method of monitoring a subject'sneurological condition is provided. The method comprises implanting adevice in the subject. In one embodiment, the device is implanted in aminimally invasive fashion. Typically, the devices are leadless and areimplanted between a subject's skull and scalp. A physiological signalsampled by the implanted devices is analyzed to determine if the subjectis in a contra-ictal condition. If the subject is in a contra-ictalcondition, an output is provided to the subject that is indicative ofthe subject being in the contra-ictal condition.

The physiological signal can be an EEG signal. The contra-ictalcondition can be a neurological state in which the subject is unlikelyto transition into an ictal condition within a time period. The timeperiod can be a predetermined time period.

Analyzing the physiological signal can comprise extracting N featuresfrom the physiological signal, generating a N-dimensional feature vectorof the extracted N features for time points of the physiological signal,and determining if the N-dimensional feature vector is within acontra-ictal cluster or region in the N-dimensional space.

For a further understanding of the nature and advantages of the presentinvention, reference should be made to the following description takenin conjunction with the accompanying drawings.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a simplified method of identifying a contra-ictal conditionin a subject data set according to one embodiment of the invention.

FIG. 1B is a simplified method of identifying a contra-ictal conditionin a subject data set according to another embodiment of the invention.

FIG. 1C is a simplified method of identifying a contra-ictal conditionin a subject data set according to yet another embodiment of theinvention.

FIG. 2 schematically illustrates a plurality of algorithms that may beembodied by the present invention.

FIG. 3 is a diagram illustrating three neurological states of epilepsy(ictal, post-ictal and inter-ictal).

FIG. 4 is a diagram illustrating the three neurological states as wellas a pre-ictal period.

FIG. 5 is a diagram illustrating the three neurological states as wellas contra-ictal and pro-ictal states.

FIG. 6 illustrates one example of a classification method in 2D featurespace.

FIGS. 7 and 8 illustrate various classification methods encompassed bythe present invention which include a contra-ictal class in 2D featurespace.

FIG. 9 illustrates a plotting of two-dimensional feature vectors in atwo-dimensional feature space with different combination of variables(features).

FIG. 10 illustrates a plotting of two-dimensional feature vectors in atwo dimensional feature space with contours indicating minimum time toseizure.

FIG. 11 is an overlay of an output from a contra-ictal classifier overan output of a pro-ictal classifier.

FIG. 12 is a sample truth chart that may be used to determine acommunication output provided to the subject.

FIG. 13 illustrates a simplified system embodied by the presentinvention which comprises one or more implantable devices incommunication with an external device.

FIG. 14 illustrates simplified methods of operating the system of thepresent invention.

FIG. 15A illustrates a bottom view of one embodiment of an activeimplantable device that is encompassed by the present invention.

FIG. 15B illustrates a cross-sectional view of the active implantabledevice of FIG. 15A along lines B-B.

FIG. 15C is a linear implantable device that comprises a plurality ofelectrode contacts in which at least one electrode contact comprises theactive implantable device of FIG. 15A.

FIG. 15D is a cross sectional view of the implantable device of FIG. 15Calong lines D-D.

FIG. 15E is a 4×4 electrode array that comprises a plurality ofelectrode contacts in which at least one electrode contact comprises theactive implantable contact of FIG. 15A.

FIG. 16A is a cross-sectional view of another embodiment of animplantable device that is encompassed by the present invention.

FIG. 16B is a cross-sectional view of another embodiment of theimplantable device in which a conductive can forms a housing around theelectronic components and acts as an electrode.

FIG. 16C illustrates a simplified plan view of an embodiment thatcomprises four electrodes disposed on the implanted device.

FIG. 17 illustrates one embodiment of the electronic components that maybe disposed within the implantable device.

FIG. 18 is a block diagram illustrating one embodiment of electroniccomponents that may be in the external device.

FIG. 19 illustrates a simplified trocar or needle-like device that maybe used to implant the implantable device beneath the subject's skin.

FIG. 20 illustrates a simplified trocar or needle-like device that maybe used to implant the implantable device within a burr hole in thesubject's skull.

FIG. 21 illustrates a method of inserting an implantable device in thesubject and wirelessly sampling EEG signals from a subject.

FIG. 22 illustrates a method of using an implantable device in thesubject to determine if the subject is in a contra-ictal condition.

FIG. 23 is a kit in accordance with embodiments of the presentinvention.

DETAILED DESCRIPTION OF THE INVENTION

Certain specific details are set forth in the following description andfigures to provide an understanding of various embodiments of theinvention. Certain well-known details, associated electronics anddevices are not set forth in the following disclosure to avoidunnecessarily obscuring the various embodiments of the invention.Further, those of ordinary skill in the relevant art will understandthat they can practice other embodiments of the invention without one ormore of the details described below. Finally, while various processesare described with reference to steps and sequences in the followingdisclosure, the description is for providing a clear implementation ofparticular embodiments of the invention, and the steps and sequences ofsteps should not be taken as required to practice this invention.

While the discussion below focuses on measuring electrical signalsgenerated by electrodes placed near, on, or within the brain or nervoussystem (EEG signals) of subjects and subject populations for thedetermination of when an epileptic subject is in a contra-ictalcondition, it should be appreciated that the invention is not limited tomeasuring EEG signals or to determining when the subject is in acontra-ictal state. For example, the invention could also be used insystems that measure one or more of a blood pressure, blood oxygenation(e.g., via pulse oximetry), temperature of the brain or of portions ofthe subject, blood flow measurements, ECG/EKG, heart rate signals,respiratory signals, chemical concentrations of neurotransmitters,chemical concentrations of medications, pH in the blood, or otherphysiological or biochemical parameters of a subject.

Furthermore, while the remaining discussion focuses on identifying acontra-ictal condition for epileptic subjects, the present invention mayalso be applicable to monitoring other neurological or psychiatricdisorders and identifying a condition or state for such disorders inwhich the subject is unlikely to experience some adverse effect. Forexample, the present invention may also be applicable to monitoring andmanagement of sleep apnea, Parkinson's disease, essential tremor,Alzheimer's disease, migraine headaches, depression, eating disorders,cardiac arrhythmias, bipolar spectrum disorders, or the like. As can beappreciated, the features extracted from the signals and used by thealgorithms will be specific to the underlying disorder that is beingmanaged. While certain features may be relevant to epilepsy, suchfeatures may or may not be relevant to the state measurement for otherdisorders.

One embodiment of the present invention identifies and uses acontra-ictal classification for each subject in which the subject ishighly unlikely to transition to the ictal state within a specified timeperiod. The contra-ictal condition can be considered to be a subset ofthe inter-ictal class or it can be considered to be a completely newneurological classification. While it is beneficial to the subject toknow if the subject is in the inter-ictal condition, being in theinter-ictal condition does not necessarily inform the subject that theywill not quickly transition from the inter-ictal condition to the ictalcondition. Being able to inform a subject that they are in acontra-ictal state can allow the subject to engage in normal dailyactivities, such as walking down a set up stairs, without fearing thatthey will have a seizure or without fearing that they may quicklytransition into a pro-ictal state. Knowing when a seizure is unlikely tooccur can be even more important to the subject's freedom than beingalerted when a seizure is likely to occur.

The period of time associated with the contra-ictal state will varydepending on the implementation of the algorithm. The period of timecould be a predetermined time period as determined from the trainingdata and programmed into the algorithm, such as 10 minutes, 20 minutes,30 minutes, 60 minutes, 90 minutes or more. In other implementations,the algorithm could compute the period, which may be different fromepisode to episode for a single subject. Thus, for some subjects, theperiod of time could span many hours or even days or weeks.

Proposed seizure prediction systems only attempt to differentiatebetween a pre-ictal state and an inter-ictal state for purposes ofseizure prediction. Advantageously, embodiments of the present inventionmay further identify the contra-ictal condition or state for theparticular subject.

FIG. 1A illustrates a simplified method of identifying a contra-ictalstate for the subject. The method of FIG. 1A is typically performed in acomputer system in a physician's office, but it could also be performedin a central processing computer workstation remote from the physician,or even in a subject's external data device or implanted communicationunit (shown in FIG. 9).

At step 2, a training dataset of the subject is obtained and annotatedto identify the ictal activity. The training data could span days orweeks, and is preferably a substantially continuous monitoring of thesubject's EEG signals using an array of scalp or intracranialelectrodes. Preferably the training data comprises a plurality of ictalevents separated by inter-ictal intervals. For epilepsy, the trainingset of physiological signals typically includes a training set ofintracranial EEG recordings from the subject's long term visit to anepilepsy monitoring unit (EMU). However, the EEG training sets could beobtained from the ambulatory system utilizing an implantable device andexternal device as described below.

While EEG signals are currently the desirable physiological signals thatare analyzed, any of the aforementioned physiological signals could beused to train the algorithms. As is known in the art, the training setmay be overlaid with comments from a physician and/or a markingalgorithm may automatically identify some or all of the ictal activityin the training set—such as epileptiform spikes, earliest electrographicchange (EEC), unequivocal electrical onset of seizure (UEO), unequivocalclinical onset (UCO), end of electrographic seizure (EES), etc. Thefollowing Steps 4-10 which are described in the subsequent paragraphsare directed towards EEG signals, however, such analysis may also beapplied to the aforementioned other physiological signals.

At step 4, N feature extractors may be applied to the training set toquantify relevant aspects of the EEG training dataset. Any number offeatures can be extracted from the EEG signals in order to assess thesubject's condition. At step 6, for each desired point in time in theEEG training dataset, an N-dimensional feature vector will be formed foreach of the N features that are extracted. At step 8, if desired, theextracted N-dimensional feature vectors may then be allocated or plottedin an N-dimensional feature space. While not shown in FIG. 1A, theinvention may also be used with lower dimension spaces created throughapplication of data transformations to the N-dimensional feature vector,including but not limited to, principle components analysis, factoranalysis, or linear discriminant analysis. For ease of reference, FIGS.3 to 8 illustrate a plot of feature vectors across a two dimensionalspace (N=2), but it should be appreciated that any dimensional spacecould be used with the present invention.

Since it is not likely for the physician or training system to identifya contra-ictal period a priori, one aspect of the present inventionutilizes an unsupervised learning protocol to identify a contra-ictalcondition for the subject by utilizing an algorithm or other means toidentify a region of the feature space or clusters or groupings offeature vectors in the N-dimensional feature space that aresubstantially devoid of feature vectors that are in an ictal conditionand for which all feature vectors in the grouping or region areseparated from an ictal event (e.g., seizure) by a predetermined timeperiod (step 10). For example, the N-dimensional feature space may bepartitioned into a collection of N-dimensional hypercubes. A hypercubethat is substantially devoid of training vectors that occur within apredetermined time period prior to the next seizure may be labeledcontra-ictal. In another implementation, a binary space partitioningalgorithm can be used to partition the N-dimensional feature space intoa collection of N-dimensional hyperprisms. A hyperprism that issubstantially devoid of training vectors that occur within apredetermined time period prior to the next seizure may be labeledcontra-ictal. In another implementation, the structure of the trainingdata may be approximated by an expansion of radial basis function, e.g.a Gaussian mixture model. Each feature vector in the training data maybe assigned to one component of the radial basis function expansionusing, e.g., Bayesian posterior probability or decision risk criteria. Acomponent that is substantially devoid of training vectors that occurwithin a predetermined time period prior to the next seizure may belabeled contra-ictal. The algorithm may also identify other classes ofinterest from the EEG training dataset (e.g., inter-ictal that is notpart of the contra-ictal class, pro-ictal, ictal, post-ictal, or thelike), and the classes of interest (or groupings of feature vectors) forthe subject and/or mathematical representations thereof are stored inmemory for later use in the subject system implanted or otherwise usedby the subject.

It is further noted that each identified partition in the N-dimensionalfeature space can be assigned an identifier that may be used torepresent states in a Markov chain, or symbols emitted by hidden statesin a hidden Markov model. These identifiers, or sequences of identifiersmay be used to make inferences about future states, and thereby thelikelihood of seizure occurrence.

Similar approaches may be used to derive and train a pro-ictalalgorithm. For example, an algorithm or other means may be used toidentify a region of the feature space or clusters or groupings offeature vectors in the N-dimensional feature space that frequentlyprecede an ictal state by a predetermined period of time but occurinfrequently in inter-ictal intervals. Alternatively, a prior artseizure prediction algorithm may be used.

FIG. 1B shows another embodiment of a method of identifying acontra-ictal state for a subject. This method tracks the method of FIG.1A for steps 2, 4, 6 and 8. FIG. 1B adds a step 9, however, thatinvolves identifying a grouping of points or a region in theN-dimensional feature space that occurs within a predetermined time ofseizure activity. This group or region is labeled “pro-ictal.” In step10 of this method, the method then identifies a grouping of points or aregion in the N-dimensional feature space that is substantially freefrom pro-ictal activity feature vectors and is separated in time fromthe pro-ictal activity by a predetermined time period using, e.g., thetechniques discussed above with respect to step 10 of FIG. 1A.

FIG. 1C shows yet another embodiment of a method of identifying acontra-ictal state for a subject. Once again, this method tracks themethod of FIG. 1A for steps 2, 4, 6 and 8. Like the method of FIG. 1B,FIG. 1C adds a step 9 that involves identifying a grouping of points ora region in the N-dimensional feature space that occurs within apredetermined time of seizure activity. This group or region is labeled“pro-ictal.” In step 10 of this method, the method then identifies agrouping of points or a region in the N-dimensional feature space thatis substantially free from both pro-ictal activity feature vectors andseizure feature vectors, and is separated in time from the seizure andpro-ictal activity by a predetermined time period using, e.g., thetechniques discussed above with respect to step 10 of FIG. 1A.

Once the algorithm has been trained to identify the different classesfor the subject, the algorithm may be embodied or otherwise uploadedinto a subject system for performing substantially real-time monitoringand assessment of the subject's brain activity. FIG. 2 depicts anexample of the overall structure of a system for performingsubstantially real-time assessment of the subject's brain activity andfor determining the communication output that is provided to thesubject. The system may comprise one or more algorithms or modules thatprocess input data 12. The algorithms may take a variety of differentforms, but typically comprises one or more feature extractors 14 a, 14b, 15 and at least one classifier 16, 17. The embodiment illustrated inFIG. 2 shows a contra-ictal algorithm 19 and a pro-ictal algorithm 20which share at least some of the same feature extractors 14 a, 14 b. Inalternative embodiments, however, the algorithms used in the system mayuse exactly the same feature extractors or completely different featureextractors (not shown).

The input data 12 is typically EEG, but may comprise representations ofphysiological signals obtained from monitoring a subject and maycomprise any one or combination of the aforementioned physiologicalsignals from the subject. The input data may be in the form of analogsignal data or digital signal data that has been converted by way of ananalog to digital converter (not shown). The signals may also beamplified, preprocessed, and/or conditioned to filter out spurioussignals or noise. For purposes of simplicity the input data of all ofthe preceding forms is referred to herein as input data 12. In onepreferred embodiment, the input data comprises between about 1 channeland about 64 channels of EEG from the subject.

The input data 12 from the selected physiological signals is supplied tothe one or more feature extractors 14 a, 14 b, 15. Feature extractor 14a, 14 b, 15 may be, for example, a set of computer executableinstructions stored on a computer readable medium, or a correspondinginstantiated object or process that executes on a computing device.Certain feature extractors may also be implemented as programmable logicor in a fixed logic device. In general, feature extractors 14 a, 14 b,15 can process data 12 and identify some characteristic of interest inthe data 12. Feature extractors used in the subject system are typicallythe same feature extractors used in the method described in the methodof FIG. 1. Such a characteristic of the data is referred to herein as anextracted feature.

Each feature extractor 14 a, 14 b, 15 may be univariate (operating on asingle input data channel), bivariate (operating on two data channels),or multivariate (operating on multiple data channels). Some examples ofpotentially useful characteristics to extract from signals for use indetermining the subject's propensity for a neurological event includebut are not limited to bandwidth limited power (alpha band [8-13 Hz],beta band [13-18 Hz], delta band [0.1-4 Hz], theta band [4-8 Hz], lowbeta band [12-15 Hz], mid-beta band [15-18 Hz], high beta band [18-30Hz], gamma band [30-48 Hz], high frequency power [>48 Hz], bands withoctave or half-octave spacings, wavelets, etc.), second, third andfourth (and higher) statistical moments of the EEG amplitudes or otherfeatures, spectral edge frequency, decorrelation time, Hjorth mobility(HM), Hjorth complexity (HC), the largest Lyapunov exponent L(max),effective correlation dimension, local flow, entropy, loss of recurrenceLR as a measure of non-stationarity, mean phase coherence, conditionalprobability, brain dynamics (synchronization or desynchronization ofneural activity, STLmax, T-index, angular frequency, and entropy), linelength calculations, first, second and higher derivatives of amplitudeor other features, integrals, and mathematical linear and non-linearoperations including but not limited to addition, subtraction, division,multiplication and logarithmic operations. Of course, for otherneurological conditions, additional or alternative characteristicextractors may be used with the systems described herein.

The extracted characteristics can be supplied to the one or moreclassifiers 16, 17. Like the feature extractors 14 a, 14 b, 15, eachclassifier 16, 17 may be, for example, a set of computer executableinstructions stored on a computer readable medium or a correspondinginstantiated object or process that executes on a computing device.Certain classifiers may also be implemented as programmable logic or ina fixed logic device.

The classifiers 16, 17 analyze one or more of the extractedcharacteristics, and either alone or in combination with each other (andpossibly other subject dependent parameters), provide a result 18 thatmay characterize, for example, a subject's condition. The output fromthe classifiers may then be used to determine the output communicationthat is provided to the subject regarding their condition. As describedabove, the classifiers 16, 17 are trained by exposing them to trainingmeasurement vectors, typically using supervised methods for knownclasses, e.g. ictal, and unsupervised methods as described above forclasses that can't be identified a priori, e.g. contra-ictal. Someexamples of classifiers include k-nearest neighbor (“KNN”), binary andhigher order space partitions, linear or non-linear regression,Bayesian, mixture models based on Gaussians or other basis functions,neural networks, and support vector machines (“SVM”). Each classifier16, 17 may provide a variety of output results, such as a logical resultor a weighted result. The classifiers 16, 17 may be customized for theindividual subject and may be adapted to use only a subset of thecharacteristics that are most useful for the specific subject.Additionally, over time, the classifiers 16, 17 may be further adaptedto the subject, based, for example, in part on the result of previousanalyses and may reselect extracted characteristics that are used forthe specific subject.

For the embodiment of FIG. 2, the pro-ictal classifier 17 may classifythe outputs from feature extractors 14 a, 14 b to detect characteristicsthat indicate that the subject is at an elevated susceptibility for aneurological event, while the contra-ictal classifier 16 may classifythe outputs from feature extractors 14 a, 14 b, 15 to detectcharacteristics that occur when the subject is unlikely to transitioninto an ictal condition for a specified period of time. The combinedoutput of the classifiers 16, 17 may be used to determine the outputcommunication provided to the subject. In embodiments which compriseonly the contra-ictal algorithm, the output from the contra-ictalclassifier 16 alone may be used to determine the output communication tothe subject.

FIG. 3 illustrates a Venn diagram illustrating a simplifiedapproximation of the relationship of the neurological states orconditions of subjects diagnosed with epilepsy. The ictal state 26 isthe actual period in which the subject is experiencing a seizure. Aspreviously mentioned, the “average” subject is in the ictal stateapproximately 0.02% of the overall time. Therefore, the associated sizesof the Venn diagram set areas are not meant to be representative of theoverall time the subject is in the various states, otherwise, the ictalperiod would be approximately 5,000 times smaller than the inter-ictalperiod. The inter-ictal state 22 is sometimes termed the “normal”neurological state and represents the neurological state betweenseizures. The post-ictal state 28 is the neurological state immediatelyfollowing a seizure or ictal 26 state. Also depicted in this three statemodel are the transitions. During the onset of a seizure theneurological state transitions 202 from the inter-ictal state to theictal state. Upon termination of the seizure the neurological statetransitions 200 to the post-ictal state and then transitions 204 to theinter-ictal state. During seizure clustering it is also possible for thesubject to transition 200 from the post-ictal state to the ictal state.

FIG. 4 illustrates an additional state, pre-ictal 27, which occursbetween the inter-ictal state and the seizure or ictal state. Someresearchers have proposed that seizures develop minutes to hours beforethe clinical onset of the seizure. These researchers therefore classifythe “pre-ictal” condition as the beginning of the ictal or seizure eventwhich begins with a cascade of events. Under this definition, a seizureis imminent and will occur (e.g. transition 203 from pre-ictal to ictal)if a pre-ictal condition is observed. There have been a number ofproposals from groups around the world for predicting seizures andwarning the subject of the impending seizure. Most of such proposalsattempt to analyze the subject's electroencephalogram orelectrocorticograms (referred to collectively as “EEGs”), todifferentiate between a “pre-ictal condition” (i.e., pre-seizurecondition) and an “inter-ictal condition” (i.e., between seizures). Todate, however, none of the proposed systems have proven to be effectivein predicting seizures. With this additional state in the state diagramof FIG. 4, we see that it is possible to transition from the post-ictalstate either to pre-ictal, inter-ictal or ictal.

FIG. 5 illustrates two additional neurological states. These states,contra-ictal and pro-ictal, are shown as subsets within the inter-ictalstate. The contra-ictal state 29 is referred to as a “low susceptibilityto seizure” condition for a time period. The pro-ictal state 24represents a neurological state having a high susceptibility for aseizure. As shown it is possible for the neurological contra-ictal stateto transition back into the general inter-ictal state (transition 218)or into a pro-ictal state (transition 216). As shown by transitions 216,222 and 202, it is possible for the neurological pro-ictal state totransition to the contra-ictal state, the inter-ictal state or the ictalstate. The subject may also go from an inter-ictal state to an ictalstate.

FIGS. 6-12 illustrate different aspects of the systems encompassed bythe present invention. The classifiers may have multiple classes (e.g.,two or more), may provide a weighted answer, or they may provide anoutput that is expressed as a continuum between the contra-ictal andpro-ictal conditions, with a scalar or vector of parameters describingthe actual condition and its variations. For example, as shown in FIG.6, a multiple class classifier may have labels such as ‘inter-ictal’ 22,‘pro-ictal’ 24, ‘ictal’ 26, or ‘post-ictal’ 28. In other embodimentsshown in FIG. 11, the classifiers 16, 17 are one-class classifiers thatcalculate probability of class membership (probability of pro-ictal,probability of contra-ictal).

Referring now to FIGS. 7 and 8, as they relate to the seizure advisorysystem, one implementation of a classification of conditions defined bythe classifiers 16, 17 includes (1) an inter-ictal class 22 (sometimesreferred to as a “normal” condition), (2) a pro-ictal class 24(sometimes referred to as an “abnormal” or “high-susceptibility toseizure” condition), (3) an ictal class 26 (sometimes referred to as a“seizure” condition), (4) a post-ictal class 28 (sometimes referred toas a “post-seizure” condition), and (5) a contra-ictal condition 29(sometimes referred to as a “low susceptibility to seizure for a timeperiod” condition). FIG. 7 illustrates the contra-ictal class 29 as asub-set of the inter-ictal class 28 while FIG. 8 illustrates thecontra-ictal class 29 as a separate class from the inter-ictal class 28.

FIG. 9 illustrates an example of 2-dimensional projections of anN-dimensional feature space extracted from subject physiological data,such as EEG data. The dark data points are feature vectors that occurwithin 20 minutes of a subsequent seizure. These data points aretherefore labeled pro-ictal. The lighter points are inter-ictal featurevectors that occur more than 3 hours prior to a seizure. As shown in theprojection onto variables 15 and 21 and variables 36 and 44 in the leftcolumn of FIG. 9, there does not appear to be any differentiableclusters or groupings between the two groups. However, for theprojection onto variable 2 and 18 and variable 1 and 34 in the rightcolumn of FIG. 9, there is a more defined separation between the twoclasses. While the pro-ictal class is included in the inter-ictal class,there are areas outlined by the dotted lines 30 in both two-dimensionalprojections that are substantially free of pro-ictal feature vectors.

The feature classification approach of FIG. 9 can be adapted to developcontra-ictal state detection algorithms for predetermined time periodsof other lengths during which a seizure is unlikely. FIG. 10 illustratesone of the 2-dimensional projections of an N-dimensional features spaceof FIG. 9 for variable 2 versus 18. Added to this 2D projection arecontour lines regarding the time elapsed prior to a seizure. For thearea marked by “A” all the feature vectors occur more than 5 minutesprior to a seizure. For the area marked by “B” all the feature vectorsoccur more than 15 minutes prior to the seizure. For areas marked by“C”, “D”, “E” all of the feature vectors occur more than 30, 60 and 90minutes prior to the seizure, respectively. Using this 2-dimensionalprojection one may also adjust/customize the green light for indicatingthe “contra-ictal” state by selecting the time to seizure contour line(e.g. 15, 30, 60, 90, etc.).

After deriving the feature vectors that may be used to classify subjectphysiological signals as being contra-ictal, pro-ictal, etc., thesefeature vectors may be used to train or form an algorithm for use in apatient monitoring device. FIGS. 11 and 12 illustrate how the outputsfrom two one-state classifiers within a trained analysis algorithm in apatient monitoring device may be used to determine the outputcommunication provided to the subject. FIG. 11 illustrates an example ofthe output from the contra-ictal classifier 40 overlaid on an outputfrom the pro-ictal classifier 42. Unlike prior art seizure monitoringdevices that looked only for features corresponding to ictal orpre-ictal activity, these classifiers classify extracted featuresagainst earlier-derived features to determine whether the extractedfeatures correspond to pro-ictal activity and whether the extractedfeatures correspond to contra-ictal activity. The right-most dotted lineindicates where the seizure started. FIG. 12 is a truth table 50 thatprocesses the outputs from the classifiers to determine the outputcommunication provided to the subject.

The truth table 50 of FIG. 12 shows the different possible combinationsof outputs from the each of the classifiers and the associated outputcommunication provided to the subject. In one simplified embodiment, thepotential output to the subject includes a green light, a yellow lightand a red light. A green light may indicate to the subject that they areat a low susceptibility to a seizure for a time period. A yellow light(or some other indication) may indicate to the subject to proceed withcaution. Such an indication does not necessarily mean that the subjectis at a high susceptibility to have a seizure, but it does mean that itis possible to have a seizure within a predetermined time (such as 90minutes, etc.). Finally, a red light (or some other indication) mayindicate to the subject that they are at an elevated susceptibility fora seizure.

It should be appreciated however, that while FIGS. 11 and 12 describeproviding an output to the subject in the form of yellow lights, greenlights and red lights, the present invention embodies any number ofdifferent type of outputs may be provided to the subject to indicatetheir condition. The subject's condition could, alternatively, beindicated by the absence of an output. For example, the system couldcomprise a yellow light and a red light, and the lack of either the redlight or yellow light being illuminated would indicate the subject is ina contra-ictal state. The outputs may be different displays on a screento the subject, different tactile outputs (e.g., vibrations), differentsounds, different lights, or any combination thereof Additionally, suchoutputs are not limited to the patient/subject, rather the output may beprovided to a caregiver. Caregivers may include a physician, nurse orrelative, or the like. Furthermore, such output may also provide theinputs to either a closed loop or open loop therapeutic response whichattempts to minimize and/or prevent a seizure occurrence. Suchtherapeutic approaches may include, without limitation, vagus nervestimulation, deep brain stimulation, neurostimulation,automated/semi-automated or manual dispensing of antiepileptic drugs,and biofeedback techniques.

Referring again to FIG. 11, at Time 1, both classifier outputs 40, 42are considered to be below an artificially specified threshold 44 andare both considered to be “low.” In this embodiment, anything below thethreshold 44 indicates that there is a low likelihood that the subjectis in a pro-ictal state and/or a low likelihood that the subject is in acontra-ictal state. Since such outputs 40, 42 from the classifiers areinconclusive and appear to conflict with each other, the outputcommunication provided to the subject may indicate that that the subjectshould proceed with caution. One example of such an output communicationis a yellow light. This output corresponds to the first row 52 of thetruth table 50 of FIG. 12.

At Time 2, the output 40 from the contra-ictal classifier is high (H)and the output from the pro-ictal classifier 42 is low (L). Such aclassification indicates that there is a low likelihood that the subjecthas an increased susceptibility for a seizure and a high likelihood ofbeing in a contra-ictal state. These classifiers appear to be consistentwith each other; consequently, the output communication provided to thesubject may indicate that the subject is in a contra-ictal state. Oneexample of such an output communication is the display of a green light.This scenario corresponds to the second row 54 of FIG. 12.

As shown in FIG. 11, the green light would stay on until Time 3 wherethe output 40 from the contra-ictal classifier is trending lower but isstill above threshold 44 (is high (H)) and the output 42 from thepro-ictal classifiers transitions to high (H). As shown in the third row56 of the truth table of FIG. 12, when both classifier outputs are high(H)—which indicates a high likelihood that the subject is at anincreased susceptibility to a seizure and a high likelihood that thesubject is in a contra-ictal condition (inconsistent outputs)—an outputcommunication is output to the patent to indicate that they shouldproceed with caution (e.g., yellow light).

Finally, at Time 4 in FIG. 11, the output 40 from the contra-ictalclassifier has fully transitioned to low (L) (e.g., low likelihood thatthe subject is in a contra-ictal state) and the output 42 from thepro-ictal classifier is above threshold 44 and is high (H) (e.g., highlikelihood that the subject is at an increased susceptibility to aseizure). This scenario corresponds with the fourth row 58 of FIG. 12and the red light would be output to the subject—which indicates thatthe subject has a high susceptibility to a seizure and should take anappropriate action.

In another embodiment shown in FIG. 11, different thresholds are usedfor the contra-ictal and pro-ictal classifiers. For example, thecontra-ictal classifier output 40 could be compared to a higherthreshold 43, while the pro-ictal classifier output 42 could be comparedto the lower threshold 44. In this example, the contra-ictal indication(e.g., green light) might be provided if the contra-ictal classifieroutput 40 exceeds the threshold 43 and if the pro-ictal classifieroutput 42 does not exceed the threshold 44; the pro-ictal indication(e.g., red light) might be provided if the contra-ictal classifieroutput 40 does not exceed threshold 43 and if the pro-ictal classifieroutput 42 exceeds threshold 44; and an indication that the outputs areinconclusive (e.g., a yellow light) if neither classifier output exceedsits threshold.

While FIGS. 11 and 12 illustrate the use of two one-class classifiers,any number and type of classifier may be used by the systems of thepresent invention. For example, in other embodiments it may be desirableto have a single classifier classify the subject as being in one ofthree conditions—an inter-ictal class, a pro-ictal class, and acontra-ictal class—which could correspond, respectively, to a normalpropensity for a future seizure, an elevated or high propensity for afuture seizure, and a low propensity for a future seizure.

In other embodiments, the output of the classification algorithm wouldindicate the existence of a contra-ictal condition (e.g., a green light)so long as the extracted feature vector corresponds only with trainingpoints that almost never preceded a seizure by less than thepredetermined time period, such as 90 minutes. The output of theclassification algorithm would indicate the existence of a pro-ictalcondition (e.g., a red light) if the extracted feature corresponds to aregion of the feature space indicative of pro-ictal state. Thisindication is not a seizure prediction; a pro-ictal condition mightresolve without a seizure ever occurring. The end of a contra-ictalindication does indicate, however, that it is no longer unlikely that aseizure will occur within 90 minutes (or other predetermined time). Inaddition, in these embodiments, while the contra-ictal indication has apredetermined time associate with it, the pro-ictal indication does not.The subject may stay in a pro-ictal state for a prolonged period oftime, or the subject might leave the pro-ictal state immediately afterentering it.

In still other embodiments, the classification algorithm for acontra-ictal indication can be derived by determining the kinds offeature vectors that never preceded a pro-ictal condition by less than apredetermined time. When trained using this kind of subject data, thiscontra-ictal classification algorithm would indicate a contra-ictalcondition (such as be lighting a green light) when a feature vectorextracted from a subject's physiological signal (such as an EEG)corresponds to one of such feature vectors, thereby indicating that thesubject is unlikely to transition to a pro-ictal state within thatpredetermined time period.

In yet other embodiments, the contra-ictal indication classificationalgorithm can be derived by determining the kinds of feature vectorsthat never preceded a pro-ictal condition by less than a predeterminedtime and never preceded a seizure by less than the predetermined time.When trained using this kind of subject data, this contra-ictalclassification algorithm would indicate a contra-ictal condition (suchas be lighting a green light) when a feature vector extracted from asubject's physiological signal (such as an EEG) corresponds to one ofsuch feature vectors, thereby indicating that the subject is unlikely totransition to either a pro-ictal state or to a seizure within thatpredetermined time period.

FIG. 13 illustrates one example of a system in which the algorithms 19,20 (FIG. 2) of the present invention may be embodied. System 60 includesone or more implantable devices 62 that are configured to sampleelectrical activity from the subject's brain (e.g., EEG signals).Suitable systems including minimally-invasive implantable devices aredescribed in commonly-owned U.S. patent application Ser. No. 11/766,742,filed Jun. 21, 2007, to Harris et al., the complete disclosure of whichis incorporated herein by reference. The implantable devices 62 may beactive (with internal power source), passive (no internal power source),or semi-passive (internal power source to power components, but not totransmit data signal). The implantable devices 62 may be implantedanywhere in the subject, but typically one or more of the devices 62 maybe implanted adjacent a previously identified epileptic focus or aportion of the brain where the focus is believed to be located. It mayalso be desirable to position one or more of the implantable devicesdistal to the epileptic focus. The system 60 is used to monitor aneurological condition of subject 62 for purposes of estimating asubject's susceptibility for a neurological event. The system 60 of theillustrated embodiment provides for substantially continuous samplingand analysis of brain wave electrical signals. Alternatively, thedevices 62 themselves may be used to help determine the location of theepileptic focus.

The physician may implant any desired number of devices in the subject.In some embodiments between about 1 and about 32 channels are provided,and preferably between about 8 and about 16 channels are provided. Asnoted above, in addition to monitoring brain signals, one or moreadditional implanted devices 62 may be implanted to measure otherphysiological signals from the subject.

While it may be possible to implant the implantable devices 62 under theskull and in or on the brain, it is preferred to implant the implantabledevices 62 in a minimally invasive fashion under at least one layer ofthe subject's scalp and above the skull. Implantable devices 62 may beimplanted between any of the layers of the scalp (sometimes referred toherein as “sub-galeal”). For example, the implantable devices may bepositioned between the skin and the connective tissue, between theconnective tissue and the epicranial aponeurosis/galea aponeurotica,between the epicranial aponeurosis/galea aponeurotica and the looseareolar tissue, between the loose areolar tissue and the pericranium,and/or between the pericranium and the calvarium. In someconfigurations, it may be useful to implant different implantabledevices 62 between different layers of the scalp.

Implantable devices 62 will typically be configured to substantiallycontinuously sample the brain activity of the groups of neurons in theimmediate vicinity of the implanted device. In some embodiments, ifplaced below the skull and in contact with the cortical surface of thebrain, the electrodes may be sized to be able to sample activity of asingle neuron in the immediate vicinity of the electrode (e.g., amicroelectrode). Typically, the implantable device 62 will beinterrogated and powered by a signal from the external device tofacilitate the substantially continuous sampling of the brain activitysignals. Sampling of the brain activity is typically carried out at arate above about 200 Hz, and preferably between about 200 Hz and about1000 Hz, and most preferably at about 400 Hz, but it could be higher orlower, depending on the specific condition being monitored, the subject,and other factors. Each sample of the subject's brain activity willtypically contain between about 8 bits per sample and about 32 bits persample, and preferably between about 12 bits per sample and about 16bits per sample. Thus, if each return communication transmission to theexternal device includes one EEG sample per transmission, and the samplerate is 400 Hz and there are 16 bits/sample, the data transfer rate fromthe implantable devices 62 to the external device 64 is at least about6.4 Kbits/second. If there are 32 implantable devices, the total datatransfer rate for the system 60 would be about 205 Kbits/second. Inalternative embodiments, it may be desirable to have the implantabledevices sample the brain activity of the subject in a non-continuousbasis. In such embodiments, the implantable devices 62 may be configuredto sample the brain activity signals periodically (e.g., once every 10seconds) or aperiodically.

Implantable device 62 may comprise a separate memory module for storingthe recorded brain activity signals, a unique identification code forthe device, algorithms, other programming, or the like.

A subject instrumented with the implanted devices 62 will typicallycarry a data collection device 64 that is external to the subject'sbody. The external device 64 would receive and store the signal from theimplanted device 62 with the encoded EEG data (or other physiologicalsignals). The external device is typically of a size so as to beportable and carried by the subject in a pocket or bag that ismaintained in close proximity to the subject. In alternativeembodiments, the device may be configured to be used in a hospitalsetting and placed alongside a subject's bed. Communication between thedata collection device 64 and the implantable device 62 typically takesplace through wireless communication. The wireless communication linkbetween implantable device 62 and external device 64 may provide acommunication link for transmitting data and/or power. External device64 may include a control module 66 that communicates with the implanteddevice through an antenna 68. In the illustrated embodiment, antenna 68is in the form of a necklace that is in communication range with theimplantable devices 62. It should be appreciated however, that theconfiguration of antenna 68 and control module 66 may be in a variety ofother conventional or proprietary forms. For example, in anotherembodiment control module 66 may be attached around an arm or belt ofthe subject, integrated into a hat, integrated into a chair or pillow,and/or the antenna may be integrated into control module 66.

In order to facilitate the transmission of power and data, the antennaof the external device and the implantable devices must be incommunication range of each other. The frequency used for the wirelesscommunication link has a direct bearing on the communication range.Typically, the communication range is between at least one foot,preferably between about one foot and about twenty feet, and morepreferably between about six feet and sixteen feet. As can beappreciated, however, the present invention is not limited to suchcommunication ranges, and larger or smaller communication ranges may beused. For example, if an inductive communication link is used, thecommunication range will be smaller than the aforementioned range.

In some situations, it may be desirable to have a wire directlyconnecting the subject-worn data collection device 64 to an interface(not shown) that could directly link up to the implanted devices 62 thatare positioned below the subject's skin. For example, the interface maytake the form of a magnetically attached transducer, as with cochlearimplants. This could enable power to be continuously delivered to theimplanted devices 62 and provide for higher rates of data transmission.

In some configurations, system 60 may include one or more intermediatetransponders (not shown) that facilitates data transmission and powertransmission between implantable device 62 and external device 64. Theintermediate transponder may be implanted in the subject or it may beexternal to the subject. If implanted, the intermediate transponder willtypically be implanted between the implantable device 62 and theexpected position of the external device 64 (e.g., in the neck, chest,or head). If external, the transponder may be attached to the subject'sskin, positioned on the subject's clothing or other body-worn assembly(e.g., eyeglasses, cellular phone, belt, hat, etc.) or in a device thatis positioned adjacent the subject (e.g., a pillow, chair headrest,etc.). The intermediate transponder may be configured to only transmitpower, only transmit data, or it may be configured to transmit both dataand power. By having such intermediate transponders, the external device64 may be placed outside of its normal communication range from theimplanted devices 62 (e.g., on a subject's belt or in a subject's bag),and still be able to substantially continuously receive data from theimplantable device 62 and/or transmit power to the implantable device62.

Transmission of data and power between implantable device 62 andexternal device 64 is typically carried out through a radiofrequencylink, but may also be carried out through magnetic induction,electromagnetic link, Bluetooth® link, Zigbee link, sonic link, opticallink, other types of wireless links, or combinations thereof.

One preferred method 61 of wirelessly transmitting data and power iscarried out with a radiofrequency link, similar to the link used withradiofrequency identification (RFID) tags. As illustrated in FIGS. 13and 14, in such embodiments, one or more radio frequency signals areemitted from the external device 64 through antenna 68 (step 143). Ifthe external device 64 is in communication range of the implantabledevices, at step 145 the radiofrequency (RF) energy signal illuminatesthe passive, implantable devices 62.

At step 147 the same RF signal interrogates the energized implantabledevice 62 to allow the implantable device to sample the desiredphysiological signal from the subject (such as an EEG signal). At step149, the implantable device samples the instantaneous EEG signal (orother physiological signal) from the subject.

At step 151, the implantable device 62 then communicates a return RFsignal to the external device 64 that is encoded with data that isindicative of the sampled EEG signal. Typically, the return RF signal isa based on the RF signal generated by the external device and includesdetectable modifications which indicate the sampled EEG signal. Forexample, the return signal is typically a backscattering of the RFsignal from the external device with the detectable modifications thatindicate the sampled EEG signal. Advantageously, such backscatteringdoes not require generation of a separate radiating signal and would notrequire an internal power source. The return RF signals may also includethe identification code of the implanted device so as to identify whichdevice the data is coming from. At step 153, the return RF signalemitted by the internal device 62 is received by the antenna 68, and theRF signal is decoded to extract the sampled EEG signal. The sampled EEGsignal may thereafter be stored in a memory of the external device 64.For embodiments in which the method is used to collect data, such datawill be stored until accessed by the subject. Typically, such data willbe analyzed on a separate device (e.g., physician's computerworkstation).

In alternative embodiments, however, in which the external device maycomprise software to analyze the data in substantially real-time, thereceived RF signal with the sampled EEG may be analyzed by the EEGanalysis algorithms to estimate the subject's brain state which istypically indicative of the subject's propensity for a neurologicalevent (step 155). The neurological event may be a seizure, migraineheadache, episode of depression, tremor, or the like. The estimation ofthe subject's brain state may cause generation of an output (step 157).The output may be in the form of a control signal to activate atherapeutic device (e.g., implanted in the subject, such as a vagusnerve stimulator, deep brain or cortical stimulator, implanted drugpump, etc.). In other embodiments, the output may be used to activate auser interface on the external device to produce an output communicationto the subject. For example, the external device may be used to providea substantially continuous output or periodic output communication tothe subject that indicates their brain state and/or propensity for theneurological event. Such a communication could allow the subject tomanually initiate therapy (e.g., wave wand over implanted vagus nervestimulator, cortical, or deep brain stimulator, take a fast acting AED,etc.) or to make themselves safe.

In preferred embodiments, the return RF signal is transmitted (e.g.,backscattered) immediately after sampling of the EEG signal to allow forsubstantially real-time transfer (and analysis) of the subject's EEGsignals. In alternate embodiments, however, the return RF signal may bebuffered in an internal memory and the communication transmission to theexternal device 64 may be delayed by any desired time period and mayinclude the buffered EEG signal and/or a real-time sampled EEG signal.The return RF signal may use the same frequency as the illumination RFsignal or it may be a different frequency as the illumination RF signal.

Unlike conventional digital implantable devices that send large packetsof stored data with each return RF communication transmission, someembodiments of the methods and devices of the present inventionsubstantially continuously sample physiological signals from the subjectand communicate in real-time small amounts of data during each return RFsignal communication. Because only small amounts of data (one or a smallnumber of sampled EEG signals from each implantable device 62) aretransmitted during each communication, a lower amount of power isconsumed and the illumination of the implanted device from the incominghigh-frequency RF signal will be sufficient to power the implantabledevice 62 for a time that is sufficient to allow for sampling of thesubject's EEG signal. Consequently, in most embodiments no internalpower source, such as a battery, is needed in the implantable device62—which further reduces the package size of the implantable device 62.

The implantable devices 62 and the external devices 64 of the presentinvention typically use an electromagnetic field/high frequencycommunication link to both illuminate the implantable device and enablehigh data transfer rates. Conventional systems typically have aninternally powered implantable device and use a slower communicationlink (e.g., that is designed for long link access delays) and transmitdata out on a non-continuous basis. In contrast, some embodiments of thepresent invention use a fast access communication link that transmits asmaller bursts of data (e.g., single or small number of EEG sample at atime) on a substantially continuous basis.

The frequencies used to illuminate and transfer data between theimplantable devices 62 and external device 64 are typically between13.56 MHz and 10 GHz, preferably between 402 MHz and 2.4 GHz, morepreferably between 900 MHz and 2.4 GHz. While it is possible to usefrequencies above 2.4 GHz, Applicants have found that it is preferred touse a frequency below 2.4 GHz in order to limit attenuation effectscaused by tissue. As can be appreciated, while the aforementionedfrequencies are the preferred frequencies, the present invention is notlimited to such frequencies and other frequencies that are higher andlower may also be used. For example, it may be desirable us use the MICS(Medical Implant Communication Service band) that is between 402-405 MHzto facilitate the communication link. In Europe, it may be desirable touse ETSI RFID allocation 869.4-869.65 MHz.

While not illustrated in FIG. 14, the system 60 of the present inventionmay also make use of conventional or proprietary forward errorcorrection (“FEC”) methods to control errors and ensure the integrity ofthe data transmitted from the implantable device 62 to the externaldevice 64. Such forward error correction methods may include suchconventional implementations such as cyclic redundancy check (“CRC”),checksums, or the like.

If desired, the data signals that are wirelessly transmitted fromimplantable device 62 may be encrypted prior to transmission to thecontrol module 66. Alternatively, the data signals may be transmitted tothe control module 66 as unencrypted data, and at some point prior tothe storage of the data signals in the control module 66 or prior totransfer of the data signals to the physician's office, the EEG data maybe encrypted so as to help ensure the privacy of the subject data.

FIGS. 16A and 16B illustrate two embodiments of the externally poweredleadless, implantable device 62 that may be used with the system 60 ofthe present invention. The implantable devices 62 of the presentinvention are preferably passive or semi-passive and are “slaves” to the“master” external device 64. The implantable devices will typicallyremain dormant until they are interrogated and possibly energized by anappropriate RF signal from the external device 64. As will be describedbelow, the implantable device 64 may have minimal electronic componentsand computing power, so as to enable a small package size for theimplantable device.

Advantageously, the embodiment illustrated in FIGS. 16A and 16B areminimally invasive and may be implanted with an introducer, trocar orsyringe-like device under local anesthesia by a physician or potentiallyeven a physician's assistant. Typically, the implanted device of FIG.16A may have a longitudinal dimension 1620 of less than about 3 cm, andpreferably between about 1 cm and about 10 cm, and a lateral dimension1622 of less than about 2 mm, and preferably between about 0.5 mm andabout 10 mm. As can be appreciated, such dimensions are merelyillustrative, and other embodiments of implanted device may have largeror smaller dimensions.

FIG. 16A illustrates an embodiment that comprises a first electrode 1624and a second electrode 1626 that are disposed on opposing ends ofhousing 1628. The first and second electrodes 1624, 1626 may be composedof platinum, platinum-iridium alloy, stainless steel, or any otherconventional material. The electrodes may include a coating or surfacetreatment such as platinum-iridium or platinum-black in order to reduceelectrical impedance. The first and second electrodes 1624, 1626 willtypically have a smooth or rounded shape in order to reduce tissueerosion and may have a surface area of about 3 mm², but otherembodiments may be smaller or larger. Since electrodes 1624, 1626 aretypically adapted to only sense physiological signals and are not usedto deliver stimulation, the surface area of the electrodes may besmaller than conventional implantable devices. The smaller electrodeshave the advantage of reducing the overall device size which can bebeneficial for improving subject comfort and reducing the risk of tissueerosion.

Housing 1628 is typically in the form of a radially symmetrical,substantially cylindrical body that hermetically seals electroniccomponents 1630 disposed within a cavity 1632. Housing 1628 may becomposed of a biocompatible material, such as glass, ceramic, liquidcrystal polymer, or other materials that are inert and biocompatible tothe human body and able to hermetically seal electronic components.Housing 1628 may have embedded within or disposed thereon one or morex-ray visible markers 33 that allow for x-ray localization of theimplantable device. Alternatively, one or more x-ray visible markers maybe disposed within the cavity 1632. Cavity 1632 may be filled with aninert gas or liquid, such as an inert helium nitrogen mixture which mayalso be used to facilitate package leakage testing. Alternatively, itmay be desirable to fill the cavity 1632 with a liquid encapsulant (notshown) that hardens around the electronic components. The liquidencapsulant may comprise silicone, urethane, or other similar materials.

While housing 1628 is illustrated as a substantially cylindrical bodywith the electrodes 1624, 1626 on opposing ends, housing may take anydesired shape and the electrodes may be positioned at anyposition/orientation on the housing 1628. For example, housing 1628 maytaper in one direction, be substantially spherical, substantially oval,substantially flat, or the like. Additionally or alternatively, the bodymay have one or more substantially planar surfaces so as to enhance theconformity to the subject's skull and to prevent rotation of theimplantable device 62. While not shown, housing 1628 may optionallyinclude a conductive electromagnetic interference shield (EMI) that isconfigured to shield the electronic components 1630 in housing 1628. TheEMI shield may be disposed on an inner surface of the housing, outersurface of the housing, or impregnated within the housing.

If desired, housing 1628 may optionally comprise an anchoring assembly(not shown) that improves the anchoring of the implantable device 62 tothe skull or the layers within the scalp. Such anchoring may be carriedout with adhesive, spikes, barbs, protuberances, suture holes, sutures,screws or the like.

In the illustrated embodiment, first electrode 1624 is disposed on afirst end of housing 1628 and is in electrical communication with theelectronic components 1630 through a hermetic feedthrough 1634.Feedthrough 1634 may be the same material as the first electrode 1624 orit may be composed of a material that has a similar coefficient ofthermal expansion as the housing 1628 and/or the first electrode 1624.Feedthrough 1634 may make direct contact with a pad (not shown) on aprinted circuit board 1636, or any other type of conventional connectionmay be used (e.g., solder ball, bond wire, wire lead, or the like) tomake an electrical connection to the printed circuit board 1636.

Second electrode 1626 may be spaced from a second, opposing end of thehousing 1628 via an elongated coil member 1638. In the illustratedembodiment, the second electrode 1626 typically comprises a protuberance1639 that is disposed within and attached to a distal end of the coilmember 1638. Coil member 1638 acts as an electrical connection betweensecond electrode and the electronic components 1630 disposed withinhousing 1628.

Coil member 1638 will typically be composed of stainless steel, a highstrength alloy such as MP35N, or a combination of materials such as aMP35N outer layer with silver core.

The illustrated embodiment shows that coil member 1638 has a largestlateral dimension (e.g., diameter) that is less than the largest lateraldimension (e.g., diameter) of housing 1628, but in other embodiments,the coil may have the same lateral dimension or larger lateral dimensionfrom housing 1628.

Coil member 1638 may also be used as an antenna to facilitate thewireless transmission of power and data between the implantable device62 and the external device 64 (or other device). In preferredembodiments, coil member 1638 may be used to receive and transmitradiofrequency signals. In alternative embodiments, however, coil member1638 may be inductively coupled to an external coil to receive energyfrom a modulating, alternating magnetic field. Unlike other conventionalimplantable devices, the RF antenna is disposed outside of the housing1628 and extends from one end of housing 1628. It should be appreciated,however, that the present invention is not limited to a substantiallycylindrical antenna extending from an end of the housing 1628 andvarious other configurations are possible. For example, it may bedesirable to wind the antenna around or within the housing 1628.Furthermore, it may be desirable to use a substantially flat antenna(similar to RFID tags) to facilitate the transmission of power and data.To facilitate implantation, such antennas may be rolled into acylindrical shape and biased to take the flat shape upon release fromthe introducer.

While not shown, it may also be desirable to provide a second antennabetween the first electrode 1624 and the housing 1628. The secondantenna may be used for power and downlink using a first frequency,e.g., 13.56 MHz, while the first antenna may be used for uplink using asecond frequency, e.g., 902-928 MHz. In such embodiments, however, theimplantable devices would need to have an internal timebase (e.g.,oscillator and a frequency synthesizer). For the embodiments that useonly a single frequency for the downlink and uplink, an internaltimebase or frequency synthesizer is not needed—and the timebaseestablished by the master (e.g., external device 64) can be used.

Coil member 1638 may be in electrical communication with the electroniccomponents 1630 with a hermetic feedthrough 1642 that extends through avia 1644 in housing 1628. Feedthrough 1642 is typically composed of amaterial that has a coefficient of thermal expansion that issubstantially similar to the material of housing 1640. Because the coilmember 1638 is outside of the housing 1628 the length of the implantabledevice 62 will be increased, but the flexible coil will be betterexposed to the RF signals and will be allowed to conform to the shape ofthe subject's skull.

Coil member 1638 is typically disposed outside of the housing 1628 anddisposed within an elongate, substantially flexible housing 1640.Compared to the more rigid housing 1628, the flexible housing 1640 isbetter able to conform to the shape of an outer surface of the subject'sskull, more comfortable for the subject and reduces the chance of tissueerosion. Flexible housing 1640 may comprise silicone, polyurethane, orthe like In the illustrated embodiment, flexible housing 1640 extendsalong the entire length of coil member 1638, but in other embodiments,flexible housing 1640 may extend less than or longer than thelongitudinal length of coil member 1638. Flexible housing 1640 willtypically have a substantially cylindrical shape, but if desired aproximal end 1646 of the cylindrical housing may be enlarged orotherwise shaped to substantially conform to a shape of the housing1628. The shaped proximal end 1646 may be adhered or otherwise attachedto the end of the housing 1640 to improve the hermetic seal of thehousing and may reduce any potential sharp edge or transition betweenthe housings 1628, 1640. While FIG. 16A only illustrates a singlelayered flexible housing, if desired, the flexible housing 1640 maycomprise a plurality of layers, and the different layers may comprisedifferent types of materials, have embedded x-ray markers, or the like.

A longitudinal length of flexible housing 1640 and the longitudinallength of the rigid housing 1628 may vary depending on the specificembodiment, but a ratio of the longitudinal length of the flexiblehousing 1640: the longitudinal length of the more rigid housing 1628 istypically between about 0.5:1 and about 3:1, and preferably betweenabout 1:1 and about 2:1. By having the longitudinal length of theflexible housing longer than the longitudinal length of the rigidhousing, advantageously the implantable device will be more comfortableand better able to conform to the outer surface of the subject's skull.In alternative embodiments, it may also be desirable to have alongitudinal length of the rigid housing 1628 be longer than thelongitudinal length of the flexible housing 1640, or in any otherdesired configuration.

Because the implantable devices 62 of the present invention consume aminimal amount of energy and use a high frequency RF coupling to powerthe device and communicate the EEG signals to the external device,unlike other conventional devices, some of the implantable devices 62 ofthe present invention will not need a ferrite core to store energy, andthe electronic components 1630 of the present invention will typicallyinclude aluminum or other MRI-safe material. Consequently, the subject'simplanted with the implantable device 62 may safely undergo MRI imaging.

FIG. 16B illustrates another embodiment of implantable device 62 that isencompassed by the present invention. The embodiment of FIG. 16B sharesmany of the same components as the embodiment of FIG. 16A, and suchcomponents are noted with the same reference numbers as FIG. 16A. Thereare, however, a few notable exceptions. Specifically, instead of havinga hermetically sealed housing, the embodiment of FIG. 16B provides aconductive body 48 that acts as both the housing for the electroniccomponents 1630 and as the second electrode. Conductive body 48 may becomposed of a metalized polymer, one or more metal or metal alloys, orother conductive material. Because body 48 is conductive, it may act asan electromagnetic interference (EMI) shield to the electroniccomponents disposed within the cavity 1632. Electrical connections tothe printed circuit board 1636 may be carried out with one or moreconductive spring conductors 1650 or other conventional lead connectors.

Feedthrough 1642 that is connected to the coil member 1638 extends fromthe end of coil member 1638 and makes an electrical connection with alead on the printed circuit board 1636. The feedthrough 1642 works inconjunction with one or more dielectric seals or spacers 52 tohermetically seal the cavity 1632. Similar to above, the cavity 1632 maybe filled with an inert gas or an encapsulant. The proximal end 1646 offlexible body 1640 may be coupled to the seals 52 and/or coupled to theconductive body 48.

As shown in the embodiment of FIG. 16B, the surface area of conductivebody 48 (e.g., the first electrode) may be larger than the surface areaof the second electrode 1626. In other embodiments, however, the surfacearea of the second electrode 1626 may have the substantially samesurface area and/or shape as the conductive body 48.

In most embodiments, the implantable devices shown in FIGS. 16A and 16Bfunction completely independent of the other implantable devices 62 andthere is no physical connection or communication between the variousdevices. If desired, however, the implantable devices 62 may bephysically coupled to each other with a connecting wire or tether and/orin communication with each other. If the plurality of implanted devices62 are in communication with one another, it may be desired to use acommunication frequency between the implanted devices 62 that isdifferent from the frequency to communicate between the implanteddevices and the external device 64. Of course, the communicationfrequency between the implanted devices 62 may also be the samefrequency as the communication frequency with the external device 64.

While FIGS. 16A and 16B illustrate a first and second electrode 1624,1626, the implantable devices 62 of the present invention are notlimited to only two electrodes. Any number of electrodes may be coupledto the implantable device in any orientation. For example, theelectrodes do not have to extend from ends of the housing, but may bepositioned anywhere along a portion of the housings 1628, 1640.Furthermore, a plurality of electrodes and their leads may be disposedalong the length of the flexible housing 1640 and/or rigid housing 1628so as to provide more than two electrodes per implantable device. Forexample, FIG. 16C illustrates a simplified embodiment in which there aretwo additional electrode 1624′, 1626′ positioned on the rigid housing1628 and flexible housing 1640, respectively. The spacing between thevarious contacts 1624, 1624′, 1626, 1626′ may vary or be the samedistance between each other. The spacing between electrodes will likelydepend on the overall length of the implantable device, but willtypically be between about 2 mm and about 20 mm and preferably bebetween about 5 mm and about 10 mm. In addition to the embodiment shownin FIG. 16C, it may be desirable to have the additional electrodes onlyon the flexible housing 1640 or only on the rigid housing 1628. Whileonly four electrodes are shown on the implanted device, it should beappreciated that any desirable number of electrodes (e.g., anywherebetween two electrodes and about sixteen electrodes) may coupled to theimplanted device.

While FIGS. 16A-16B illustrate some currently preferred embodiments ofthe implantable device 62, the present invention further encompassesother types of minimally invasive implantable devices 62 that canmonitor the brain activity and other physiological signals from thesubject. For example, a plurality of electrodes might reside on a singlelead that could be tunneled under the scalp from a single point ofentry. Examples of such embodiments are shown in FIGS. 15A-15E.

Such implantable devices 62 include an active electrode contact 400 thatis in communication with one or more passive electrode contacts 401. Theactive electrode contact 400 may be used to facilitate monitoring of thephysiological signals using the array of active and passive electrodecontacts. The arrays of electrode contacts may be arranged in a linearorientation (FIG. 15C) or in a grid pattern (FIG. 15E), or any otherdesired pattern (e.g., circular, star pattern, customized asymmetricpattern, etc.) For example, if the implantable device comprises twoelectrode contacts (e.g., one active contact and one passive contact),such an embodiment would have a similar configuration as the embodimentof FIG. 16A. Similarly, if the implantable device were to have foursubstantially linearly positioned electrode contacts (e.g., one activecontact and three passive contacts), such an embodiment would besubstantially similar to the configuration shown in FIG. 16C.

FIG. 15A illustrates a bottom view of an active electrode contact 400that may be part of the implantable device 62 of the present invention.The active electrode contact comprises a base 402 that is coupled to acontact portion 404. The base 402 and contact portion may be composed ofany number of different types of materials, such as platinum,platinum-iridium alloy, stainless steel, or any other conventionalmaterial. In preferred embodiments, both the base 402 and contactportion 404 are formed to their desired shape. The base 402 may comprisea plurality of hermetic feedthroughs 413 that is implemented usingconventional glass metal seal technology (e.g., pins 408, glass seal414, and vias 406). The hermetic feedthroughs 413 may be used to connectto an antenna (not shown) for communication with the external device 64or to make an electrical connection with an adjacent passive electrodecontact 401 in the implanted device 62. In the illustrated embodiment,base 402 comprises four hermetic feedthroughs 413. But as can beappreciated the base 402 may comprise any desired number of feedthroughs413 (e.g., anywhere between two and sixty four feedthroughs).

FIG. 15B illustrates a cross-sectional view of the active electrodecontact 400 along lines B-B in FIG. 15A. As shown in FIG. 15B, thecontact portion 404 is shaped to as to align the base 402 along a bottomsurface defined by flanges 409. Base 402 may be coupled to the contactportion 404 with a laser weld, glass metal seal, or other conventionalconnector 410 along an outer perimeter of the base 402 to hermeticallyseal components of the active electrode contact within a cavity 412defined by the base 402 and contact portion 404. If desired, the cavity412 may be backfilled with nitrogen and/or helium to facilitate packageleak testing.

A thin or thick filmed microcircuit or a printed circuit board (“PCB”)416 may be mounted onto an inner surface of the base 402. PCB 416 mayhave active components 418 (e.g., integrated circuits, ASIC, memory,etc.) and passive components 420 (e.g., resistors, capacitors, etc.)mounted thereto. Leads or bond wires 422 from the active and passivecomponents may be electrically attached to pads on the PCB (not shown)which make electrical connections to leads or bond wires 424 that areattached to the hermetic feedthroughs 413. While not shown in FIG. 15B,the active electrode contact 400 may comprise a rechargeable ornon-rechargeable power supply (e.g., batteries), and/or x-ray visiblemarkers (not shown).

As noted above, the active contacts may be used in conjunction with oneor more passive contacts to form an active implantable device 62 tofacilitate monitoring of the subject's physiological signals and tocommunicate with the external device 64. FIGS. 15C and 15D illustrate anembodiment of the implantable device 62 in which one active contact 400is housed in a body 426 along with a plurality of passive contacts 401to form a multiple contact implantable device 62. The contact portion ofthe active contact 400 is exposed through an opening in the body 426 toallow for sampling of the physiological signals (e.g., EEG) from thesubject. The body 426 may be substantially flexible or rigid and mayhave similar dimensions and/or shapes as the embodiments shown in FIGS.16A-16C. Body 426 may be composed of a biocompatible material such assilicone, polyurethane, or other materials that are inert andbiocompatible to the human body. Body 426 may also be composed of arigid material such as polycarbonate. The implantable device may beinjected into the subject using the introducer assembly shown in FIG. 19and methods shown in FIG. 20.

As shown in FIG. 15D wire leads 427 may extend from the passive contacts401 and be electrically and physically coupled to one of the hermeticfeedthroughs 413 of the active contact 400 to facilitate sampling of thephysiological signals using all four electrode contacts. For embodimentswhich use a wireless link (e.g., RF) to wirelessly transmit data to theexternal device 64 and optionally to power the device, one of thefeedthroughs may be coupled to an antenna 428 that is configured towirelessly communicate with the external device. It should beappreciated, that while not described herein, the embodiments of FIGS.15C-15E may have any of the components or variations as described abovein relation to FIGS. 16A-16B.

FIG. 15E illustrates an alternative embodiment of the implantable device62 in which the implantable device 62 is in the form of a 4×4 grid arrayof active and passive contacts. At least one of the electrode contactsmay be an active contact 400 so as to facilitate monitoring of thesubject's physiological signals with the array. In the illustratedembodiment, the contacts in the leftmost column (highlighted withcross-hatching) are active electrode contacts 400, and the contacts inremaining column are electrically connected to one of the activecontacts 400. Of course, any number of active contacts 400 and passivecontacts 401 may be in the grid array and the active contact(s) 400 maybe positioned anywhere desired. For example, if the active electrodecontact 400 has sixteen or more hermetic feedthroughs, only one of thecontacts in the array needs to be active and the remaining fifteencontacts could be passive contacts.

FIG. 17 illustrates one simplified embodiment of the electroniccomponents 1630 (e.g., active components 418 and passive components 420in FIG. 15B) that may be disposed in the implantable devices 62 as shownin FIGS. 15A-16C. It should be appreciated, however, that the electroniccomponents 1630 of the implantable device 62 may include any combinationof conventional hardware, software and/or firmware to carry out thefunctionality described herein. For example, the electronic components1630 may include many of the components that are used in passive RFintegrated circuits.

The first and second electrodes will be used to sample a physiologicalsignal from the subject—typically an EEG signal 1753, and transmit thesampled signal to the electronic components 1630. While it may bepossible to record and transmit the analog EEG signal to the externaldevice, the analog EEG signal will typically undergo processing beforetransmission to the external device 64. The electronic componentstypically include a printed circuit board that has, among others, anamplifier 1754, one or more filters 1756 (e.g., bandpass, notch,lowpass, and/or highpass) and an analog-to-digital converter 1758. Insome embodiments, the processed EEG signals may be sent to atransmit/receive sub-system 60 for wireless transmission to the externaldevice via an antenna (e.g., coil member 1638). Additional electroniccomponents that might be useful in implantable device 62 may be found inU.S. Pat. Nos. 5,193,539, 5,193,540, 5,312,439, 5,324,316, 5,405,367 and6,051,017.

In some alternative embodiments of the present invention, the electroniccomponents 1630 may include a memory 1764 (e.g., RAM, EEPROM, Flash,etc.) for permanently or temporarily storing or buffering the processedEEG signal. For example, memory 1764 may be used as a buffer totemporarily store the processed EEG signal if there are problems withtransmitting the data to the external device. For example, if theexternal device's power supply is low, the memory in the external deviceis removed, or if the external device is out of communication range withthe implantable device, the EEG signals may be temporarily buffered inmemory 1764 and the buffered EEG signals and the current sampled EEGsignals may be transmitted to the external device when the problem hasbeen corrected. If there are problems with the transmission of the datafrom the implantable device, the external device may be configured toprovide a warning or other output signal to the subject to inform themto correct the problem. Upon correction of the problems, the implantabledevice may automatically continue the transfer the temporarily buffereddata and the real-time EEG data to the memory in the external device.

The electronic components 1630 may optionally comprise dedicatedcircuitry and/or a microprocessor 1762 (referred to herein collectivelyas “microprocessor”) for further processing of the EEG signals prior totransmission to the external device. The microprocessor 1762 may executeEEG analysis software, such as a seizure prediction algorithm, a seizuredetection algorithm, safety algorithm, or portions of such algorithms,or portions thereof. For example, in some configurations, themicroprocessor may run one or more feature extractors that extractfeatures from the EEG signal that are relevant to the purpose ofmonitoring. Thus, if the system is being used for diagnosing ormonitoring epileptic subjects, the extracted features (either alone orin combination with other features) may be indicative of the subject'ssusceptibility to or protection from a neurological event (e.g.,pro-ictal or contra-ictal). Once the feature(s) are extracted, themicroprocessor 1762 may send the extracted feature(s) to thetransmit/receive sub-system 1760 for the wireless transmission to theexternal device and/or store the extracted feature(s) in memory 1764.Because the transmission of the extracted features is likely to includeless data than the EEG signal itself, such a configuration will likelyreduce the bandwidth requirements for the communication link between theimplantable device 62 and the external device 64. Since the extractedfeatures do not add a large amount of data to the data signal, in someembodiments, it may also be desirable to concurrently transmit both theextracted feature and the EEG signal. A detailed discussion of variousembodiments of the internal/external placement of such algorithms aredescribed in commonly-owned U.S. patent application Ser. No. 11/322,150,filed Dec. 28, 2005 to Bland et al., the complete disclosure of which isincorporated herein by reference.

While most embodiments of the implantable device 62 are passive and donot need an internal power source or internal clock, in someembodiments, the electronic components 1630 may include a rechargeableor non-rechargeable power supply 1766 and an internal clock (not shown).The rechargeable or non-rechargeable power supply may be a battery, acapacitor, or the like. The rechargeable power supply 1766 may also bein communication with the transmit/receive sub-system 1760 so as toreceive power from outside the body by inductive coupling,radiofrequency (RF) coupling, etc. Power supply 1766 will generally beused to provide power to the other components of the implantable device62. In such embodiments, the implanted device may generate and transmitits own signal with the sampled EEG signal for transmission back to theexternal device. Consequently, as used herein “transmit” includes bothpassive transmission of a signal back to the external device (e.g.,backscattering of the RF signal) and internal generation of a separatesignal for transmission back to the external device.

FIG. 18 is a simplified illustration of some of the components that maybe included in external device 64. Antenna 68 and a transmit/receivesubsystem 70 will receive a data signal that is encoded with the EEGdata (or other physiological data) from the antenna 1738 of theimplantable device 62 (FIG. 17). As used herein, “EEG data” may includea raw EEG signal, a processed EEG signal, extracted features from theEEG signal, an answer from an implanted EEG analysis software (e.g.,safety, prediction and/or detection algorithm), or any combinationthereof.

The EEG data may thereafter be stored in memory 1872, such as a harddrive, RAM, permanent or removable Flash Memory, or the like and/orprocessed by a microprocessor 1874 or other dedicated circuitry.Microprocessor 1874 may be configured to request that the implantabledevice perform an impedance check between the first and secondelectrodes and/or other calibrations prior to EEG recording and/orduring predetermined times during the recording period to ensure theproper function of the system.

The EEG data may be transmitted from memory 1872 to microprocessor 1874where the data may optionally undergo additional processing. Forexample, if the EEG data is encrypted, it may be decrypted. Themicroprocessor 1874 may also comprise one or more filters that filterout high-frequency artifacts (e.g., muscle movement artifacts, eye-blinkartifacts, chewing, etc.) so as to prevent contamination of the highfrequency components of the sampled EEG signals. In some embodiments,the microprocessor may process the EEG data to measure the subject'sbrain state, detect seizures, predict the onset of a future seizure,generate metrics/measurements of seizure activity, or the like. A morecomplete description of seizure detection algorithms, seizure predictionalgorithms, and related components that may be implemented in theexternal device 64 may be found in pending, commonly-owned U.S. patentapplication Ser. Nos. 11/321,897 and 11/321,898, filed on Dec. 28, 2005,to Leyde et al. and DiLorenzo et al., and Ser. No. 12/020,450, filed onJan. 25, 2008, to Snyder et al., the complete disclosures of which areincorporated herein by reference.

It should be appreciated, however, that in some embodiments some or allof the computing power of the system of the present invention may beperformed in a computer system or workstation 1876 that is separate fromthe system 60, and the external device 64 may simply be used as a datacollection device. In such embodiments, the personal computer 1876 maybe located at the physician's office or at the subject's home and theEEG data stored in memory 1872 may be uploaded to the personal computer1876 via a USB interface 1878, removal of the memory (e.g., Flash Memorystick), or other conventional communication protocols, and minimalprocessing may be performed in the external device 64. In suchembodiments, the personal computer 1876 may contain the filters,decryption algorithm, EEG analysis software, such as the contra-ictalalgorithm, pro-ictal algorithm, and/or detection algorithm, reportgeneration software, or the like. Some embodiments of the presentinvention may take advantage of a web-based data monitoring/datatransfer system, such as those described in U.S. Pat. Nos. 6,471,645 and6,824,512, the complete disclosures of which are incorporated herein byreference.

External device 64 may also comprise an RF signal generator 1875 that isconfigured to generate the RF field for interrogating and optionallypowering the implanted devices 62. RF generator 1875 will be undercontrol of the microprocessor 1874 and generate the appropriate RF fieldto facilitate monitoring and transmission of the sampled EEG signals tothe external device.

External device 64 will typically include a user interface 1880 fordisplaying outputs to the subject and for receiving inputs from thesubject. The user interface may comprise outputs such as auditorydevices (e.g., speakers) visual devices (e.g., LCD display, LEDs toindicate brain state or propensity to seizure), tactile devices (e.g.,vibratory mechanisms), or the like, and inputs, such as a plurality ofbuttons, a touch screen, and/or a scroll wheel.

The user interface may be adapted to allow the subject to indicate andrecord certain events. For example, the subject may indicate thatmedication has been taken, the dosage, the type of medication, mealintake, sleep, drowsiness, occurrence of an aura, occurrence of aneurological event, or the like. Such inputs may be used in conjunctionwith the recorded EEG data to improve the analysis of the subject'scondition and determine the efficacy of the medications taken by thesubject.

The LCD display of the user interface 80 may be used to output a varietyof different communications to the subject including, status of thedevice (e.g., memory capacity remaining), battery state of one or morecomponents of system, whether or not the external device 64 is withincommunication range of the implantable devices 62, brain stateindicators (e.g., a warning (e.g., seizure warning), a prediction (e.g.,seizure prediction), unknown brain state, safety indication, arecommendation (e.g., “take drugs”), or the like). Of course, it may bedesirable to provide an audio output or vibratory output to the subjectin addition to or as an alternative to the visual display on the LCD. Inother embodiments, the brain state indicators may be separate from theLCD display to as to provide a clear separation between the devicestatus outputs and the brain state indicators. In such embodiments, theexternal device may comprise different colored LEDs to indicatedifferent brain states. For example, a green LED may indicate a safebrain state, a yellow light may indicate an unknown brain state, and ared light may indicate either a seizure detection or seizure prediction.

As noted above and illustrated in FIG. 9, the external device 64 maycomprise a plurality of LEDs to provide a substantially continuous,real-time indication to the subject of their condition. In theillustrated embodiment, the LEDs may include three LEDs—a green LED, ayellow LED, and a red LED. While not shown, it may also be desirable toprovide additional LEDs of different colors or additional LEDs in eachcolor to indicate a graded condition. As stated above, the period oftime associated with a contra-ictal state can be a predetermined timeperiod. There can also be multiple predetermined periods of varyingduration. The external device could therefore comprise a plurality ofoutputs which indicate one of the multiple predetermined contra-ictalperiods of time. For example, it may be desirable to illuminate two ormore green lights when the subject is in a condition that is determinedto be even more unlikely to experience a seizure. More specifically, onegreen light illuminated could indicate a contra-ictal period duration of10 minutes, whereas two green lights illuminated could indicate acontra-ictal period of 20 minutes. Or a slowly blinking green lightcould indicate a longer contra-ictal period than a rapidly blinkinggreen light. On the other extreme, but similarly, it may be desirable toprovide, and illuminate, two or more red lights when a seizure isdetected or is imminent.

The external device 64 may also include a medical grade power source1882 or other conventional power supply that is in communication with atleast one other component of external device 64. The power source 1882may be rechargeable. If the power source 1882 is rechargeable, the powersource may optionally have an interface for communication with a charger1884. While not shown in FIG. 18, external device 64 will typicallycomprise a clock circuit (e.g., oscillator and frequency synthesizer) toprovide the time base for synchronizing external device 64 and theimplantable device(s) 62. In preferred embodiments, the implantabledevice(s) 62 are slaves to the external device and the implantabledevices 62 will not have to have an individual oscillator and afrequency synthesizer, and the implantable device(s) 62 will use the“master” clock as its time base. Consequently, it may be possible tofurther reduce the size of the implantable devices 62.

In use, one or more of the implantable devices 62 are implanted in thesubject. The implanted device 62 is interrogated and powered so that theEEG signals are sampled from the subject's brain. The EEG signals areprocessed by the implanted device and the processed EEG signals arewirelessly transmitted from the implanted device(s) to an externaldevice. The EEG signals are stored for future or substantially real-timeanalysis.

The EEG analysis systems shown in FIG. 2, however, may be embodied in adevice that is implanted in the subject's body, external to thesubject's body, or a combination thereof. For example, in one embodimentthe algorithm system may be fully stored in and processed by the device62 that is implanted in the subject's body. In such embodiments, thesubject's propensity for neurological event characterization (orwhatever output is generated by the classifiers) is calculated in theimplantable device 62 and a data signal is transmitted to the externaldevice. The external processor performs any remaining processing togenerate and provide the communication output to the subject. Suchembodiments have the benefit of maintaining processing within thesubject, while reducing the communications demands on the implantabledevice 62.

In other embodiments, the signals 103 sampled from the subject may bepartially processed in the implantable device 62 before transmittingdata to the external device 64 so as to reduce the total amount of datato be transmitted, thereby reducing the power demands of thetransmit/receive subsystem 120. Examples include: digitally compressingthe signals before transmitting them; encrypting the signals; selectingonly a subset of the measured signals for transmission; selecting alimited segment of time and transmitting signals only from that timesegment; extracting salient characteristics of the signals, transmittingdata representative of those characteristics rather than the signalsthemselves, and transmitting only the result of classification. Furtherprocessing and analysis of the transmitted data may take place in theexternal device 64.

In yet other embodiments, it may be possible to perform some of thesignal processing in the implantable device 62 and some of the signalprocessing in the external device 64. For example, one or morecharacteristics from the one or more signals may be extracted withfeature extractors in the implantable device 62. Some or all of theextracted characteristics may be transmitted to the external device 64where the characteristics may be classified to assess the subject'ssusceptibility for a neurological event. If desired, external device 64may be tailored to the individual subject. Consequently, the classifiermay be adapted to allow for transmission or receipt of only thecharacteristics from the implantable device 62 that are useful for thatindividual subject. Advantageously, by performing feature extraction inthe implantable device 62 and classification in an external device atleast two benefits may be realized. First, the amount of wireless datatransmitted from the implantable device 62 to the external device 64 isreduced (versus transmitting pre-processed data). Second,classification, which embodies the decision or judgment component, maybe easily reprogrammed or custom tailored to the subject without havingto reprogram the implantable device 62.

In yet another embodiment, feature extraction may be performed externalto the body. Pre-processed signals (e.g., filtered, amplified, convertedto digital) may be transcutaneously transmitted from implantable device62 to the external device 64 where one or more characteristics areextracted from the one or more signals with feature extractors. Some orall of the extracted characteristics may be transcutaneously transmittedback into the implantable device 62, where a second stage of processingmay be performed on the characteristics, such as classifying of thecharacteristics (and other signals) to characterize the subject'spropensity for the onset of a future neurological event. If desired, toimprove bandwidth, the classifier may be adapted to allow fortransmission or receipt of only the characteristics from the subjectcommunication assembly that are predictive for that individual subject.Advantageously, because feature extractors may be computationallyexpensive and energy hungry, it may be desirable to have the featureextractors external to the body, where it is easier to provide moreprocessing and larger power sources.

Other details of devices useful for practicing the invention may befound in co-pending and commonly-owned U.S. patent application Ser. No.12/020,507, filed Jan. 25, 2008, titled “METHODS AND SYSTEMS FORMEASURING A PATIENT'S SUSCEPTIBILITY TO A SEIZURE,” the disclosure ofwhich is incorporated herein by reference.

One particular advantage of some of the embodiments of the presentinvention is the ability to provide a substantially continuous,substantially real-time indication to the subject of their neurologicalcondition. In other embodiments of the present invention, the subjectmay be provided with an indication of their neurological condition on anon-continuous basis. For example, in some embodiments it may bedesirable to only provide an output to the subject when there is achange in their condition or if the subject enters a high susceptibilityor low susceptibility condition. The ability to inform the subject thatthey are unlikely to transition to an ictal condition within a period oftime will reduce the uncertainty that effects every aspect of their dayto day life and opens up the possibility for the subject to performtasks that most people take for granted.

Such a system would further enable use of novel therapies to prevent theoccurrence of the neurological event. Therapies include automatic ormanual delivery of anti-epileptic drugs, vagus nerve stimulation, brainstimulation, etc. Some potential therapies are described incommonly-owned U.S. patent application Ser. Nos. 10/889,844 filed Jul.12, 2004 to DiLorenzo and Ser No. 11/321,898, filed Dec. 28, 2005 toLeyde et al., the complete disclosure of which is incorporated herein byreference.

As noted above, in preferred embodiments, the implantable devices areimplanted in a minimally invasive fashion under the subject's scalp 192and above an outer surface of the skull 191. FIG. 19 illustrates asimplified introducer assembly 90 that may be used to introduce theimplantable devices into the subject. The introducer assembly 90 istypically in the form of a cannula and stylet or a syringe-like devicethat can access the target area and inject the implanted device underthe skin 193 of the subject. As noted above, the implantable devices 62are preferably implanted beneath at least one layer of the subject'sscalp 192 and above the subject's skull 191. Because of the small sizeof the implantable devices 62, the devices may be injected into thesubject under local anesthesia in an out-subject procedure by thephysician or neurologist. Because the implantable devices are implantedentirely beneath the skin 193 infection risk would be reduced and therewould be minimal cosmetic implications. Due to the small size of theimplantable devices 62, it may be desirable to have a plurality ofimplantable devices pre-loaded into a sterile introducer assembly 90 orinto a sterile cartridge (not shown) so as to minimize the risk ofcontamination of the implantable devices 62 prior to implantation.

While FIG. 19 illustrates one system for implanting the implantabledevices in the subject and using the implantable devices to monitor thesubject's EEG, a variety of other non-invasive and invasive implantationand monitoring methods may be used. For example, while minimallyinvasive monitoring may be preferred, the systems and methods disclosedherein may also be applicable to more invasive monitoring. Thus, if itis desired to monitor and record intracranial EEG signals (e.g., ECoG),then it may be possible to implant one or more of the implantabledevices inside the subject's skull 191 (e.g., in the brain, above orbelow the dura mater, or a combination thereof) through a burr holecreated in the subject's skull.

In a more invasive system shown in FIG. 20, the implantable devices 62may be placed in a burr hole 2000 or groove that extends partiallythrough the skull 191 or completely through the skull 191 to monitor thesubject's brain activity. In such embodiments, the implantable devices62 may use the anchoring assembly (not shown) to mount itself to thesubject's skull 191 within the burr hole 2000. While not shown in FIG.20, it may also be desirable to place the implantable devices 62underneath the skull 191 in an epidural or subdural space.

FIG. 21 schematically illustrates one example of a minimally invasivemethod 2100 of implanting the implantable devices for ambulatorymonitoring of a subject's EEG signals. At step 2102, an incision is madein the subject's scalp. At step 2104, an introducer assembly is insertedinto the incision and a distal tip of the introducer assembly ispositioned at or near the target site. Of course, the introducerassembly itself may be used to create the incision. For example, if theintroducer assembly is in the form of a syringe, the syringe tip may bemade to create the incision and steps 2102 and 2104 may be consolidatedinto a single step. At step 2106, the introducer assembly is actuated toinject the implantable device 62 to the target site. If desired, theintroducer may be repositioned to additional target sites underneath thesubject's skin and above the skull. If needed, additional incisions maybe created in the subject's skin to allow for injection of theimplantable device 62 at the additional target sites. After a desirednumber of implantable devices are placed in the subject, at step 2108the introducer assembly is removed from the target site. At step 2110,the implantable devices are activated and used to perform long termmonitoring of the subject's EEG signals from each of the target sites.At step 2112, the sampled EEG signals are then wirelessly transmitted toan external device. At step 2114, the sampled EEG signals may then bestored in a memory in the external device or in another device (e.g.,personal computer). If desired, the EEG signals may then be processed inthe external device or in a personal computer of the physician. In oneexemplary embodiment, the EEG data collected from the subject may beused to identify the subject's contra-ictal state, step 2116 (FIG. 1).

While not shown in FIG. 20, it may also be desirable to anchor theimplantable devices to the subject to reduce the likelihood that theimplantable devices are dislodged from their desired position. Anchoringmay be performed with tissue adhesive, barbs or other protrusions,sutures, or the like.

Advantageously, the implantable devices in accordance with someembodiments are able to monitor EEG signals from the subject without theuse of burr holes in the skull or implantation within the brain—whichsignificantly reduces the risk of infection for the subject and makesthe implantation process easier. While there is some attenuation of theEEG signals and movement artifacts in the signals, because theimplantable devices are below the skin, it is believed that there willbe much lower impedance than scalp electrodes. Furthermore, having acompact implantable device 62 below the skin reduces common-modeinterference signals which can cause a differential signal to appear dueto any imbalance in electrode impedance and the skin provides someprotection from interference caused by stray electric charges (static).

As shown in FIG. 22, once implanted in the subject (step 2202), themonitoring systems 60 may be used to monitor the subject'ssusceptibility to a seizure (or other neurological event). To monitorthe subject's susceptibility to a seizure, the implanted leadlessdevices are activated to sample physiological signals (e.g., EEG) fromthe subject using the methods described above, step 2204. A signal istransmitted from the implanted leadless devices to the external device,step 2205. The signal may comprise the EEG data or other similar data.Such a signal may include the EEG signal, features extracted from theEEG signal, a classification output, or the like.

The EEG signal from the subject may be processed (either in theimplanted devices and/or in the external device) to estimate thesubject's susceptibility to a seizure, step 2206. As described above inFIGS. 2 to 8, the EEG signals may be processed to determine if thesubject is in a pro-ictal condition, inter-ictal condition, contra-ictalcondition, or the like.

While FIG. 22 illustrates using the external device to provide an outputto the subject, in some embodiments, the seizure advisory system may becompletely implanted, and a transponder or other implanted device may beused to provide an audio or tactile feedback to the subject thatindicates that they are in the contra-ictal condition. In preferredembodiments, the processing determines if the subject is in thecontra-ictal condition, step 2208. If the subject is in the contra-ictalcondition, a communication is provided to the subject with the externaldevice to indicate that the subject is in the contra-ictal condition,step 2210. The communication may be in the form of LEDS (e.g., greenLED) or other visual output, an audio output, a tactile output, or somecombination thereof.

While not shown in FIG. 22, the methods of the present invention mayalso be configured to provide a substantially continuous output of thesubject's susceptibility to a seizure, and if the subject is at anincreased susceptibility to a seizure or normal susceptibility, themethods of the present invention will provide such a communication tothe subject and/or initiate therapy.

FIG. 23 illustrates a packaged system or kit 300 that is encompassed bythe present invention. The packaged system 300 may include a package 302that has one or more compartments for receiving an introducer assembly304, one or more implantable devices 62, and an external device 64. Theintroducer assembly 304 may be provided in the form of a syringe-likedevice or a cannula and stylet, as described above with respect to FIGS.15A-15B. The implantable device 62 may include any of the embodimentsdescribed herein. One or more of the implantable devices 62 may bepre-loaded within the introducer assembly 304. In other embodiments, theimplantable devices 62 may be loaded in its separate sterile packaging(shown in dotted lines) for easy loading into the introducer assembly304. The packaged system 300 may include instructions for use (“IFU”)306 that describe any of the methods described herein.

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. For example, thepresent invention also encompasses other more invasive embodiments whichmay be used to monitor the subject's neurological system.

Alternative embodiments of the implantable device of the presentinvention may require a neurosurgeon to create a more invasive incisionin the subject's scalp. For example, it may be desirable to use a lowprofile device that is not substantially cylindrical, but instead issubstantially planar or concave so as to conform to the curvature of thesubject's skull. Such embodiments would likely not be able to beimplanted without general anesthesia and may require a surgeon toimplant the device.

On the other hand, in some embodiments it may be desirable to becompletely non-invasive. Such embodiments include “implantable” devices62 that are not actually implanted, but instead are “wearable” and maybe attached to the outer surface of the skin with adhesive or a bandageso as to maintain contact with the subject's skin. For example, it maybe possible to surface mount the device 62 behind the ears, in thescalp, on the forehead, along the jaw, or the like. Because theelectrodes are wireless and are such a small size, unlike conventionalelectrodes, the visual appearance of the electrodes will be minimal.

Furthermore, in some embodiments, it may be desirable to modify theimplantable device 62 to provide stimulation to the subject. In suchembodiments, the implantable device 62 will include a pulse generatorand associated hardware and software for delivering stimulation to thesubject through the first and second electrodes 1624, 1626 (or otherelectrodes coupled to the device. In such embodiments, the externaldevice 64 may include the hardware and software to generate the controlsignals for delivering the electrical stimulation to the subject.

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. For example, whileembodiments described above indicate that power to the implanted devicesmay be derived wirelessly from an external device and/or from a batteryin the implanted device, it should be appreciated that the internaldevices may derive or otherwise “scavenge” power from other types ofconventional or proprietary assemblies. Such scavenging methods may beused in conjunction with the external power source and/or the internalpower source, or it may be used by itself to provide the necessary powerfor the implanted devices. For example, the implanted devices mayinclude circuitry and other assemblies (e.g., a microgenerator) thatderive and store power from subject-based energy sources such as kineticmovement/vibrations (e.g., gross body movements), movement of organs orother bodily fluids (e.g., heart, lungs, blood flow), and thermalsources in the body (e.g., temperature differences and variations acrosstissue). As can be imagined, such technology could reduce or eliminatethe need for recharging of an implanted battery, replacement of adepleted battery, and/or the creation of an external RF field—and wouldimprove the ease of use of the devices by the subjects.

Some embodiments of the monitoring system may include an integralpatient diary functionality. The patient diary may be a module in theexternal device and inputs by the subject may be used to providesecondary inputs to provide background information for the sampled EEGsignals. For example, if a seizure is recorded, the seizure diary mayprovide insight regarding a trigger to the seizure, or the like. Thediary may automatically record the time and date of the entry by thesubject. Entries by the subject may be a voice recording, or throughactivation of user inputs on the external device. The diary may be usedto indicate the occurrence of an aura, occurrence of a seizure, theconsumption of a meal, missed meal, delayed meal, activities beingperformed, consumption of alcohol, the subject's sleep state (drowsy,going to sleep, waking up, etc.), mental state (e.g., depressed,excited, stressed), intake of their AEDs, medication changes, misseddosage of medication, menstrual cycle, illness, or the like. Thereafter,the subject inputs recorded in the diary may also be used by thephysician in assessing the subject's epilepsy state and/or determine theefficacy of the current treatment. Furthermore, the physician may beable to compare the number of seizures logged by the subject to thenumber of seizures detected by the seizure detection algorithm.

It is intended that the following claims define the scope of theinvention and that methods and structures within the scope of theseclaims and their equivalents be covered thereby.

What is claimed is:
 1. A neurological monitoring system comprising: animplantable device; and an external transmission assembly configured todeliver power to the implantable device and to receive a wireless datasignal from the implantable device, the implantable device comprising aprocessing assembly for sampling a neurological signal from a subject, apower assembly for receiving power from the external transmissionassembly, and a communication assembly for transmitting the wirelessdata signal from within a subject's body to the external transmissionassembly, said wireless data signal being encoded with data indicativeof the sampled neurological signal, the processing assembly beingconfigured to process the wireless data signal from the implantabledevice to determine if the subject is in a contra-ictal condition, saidcontra-ictal condition being a neurological state in which the subjectis unlikely to transition into an ictal condition within a time period.2. The neurological monitoring system of claim 1, further comprising auser interface configured to provide an output to the subject thatindicates that the subject is in the contra-ictal condition.
 3. Theneurological monitoring system of claim 2, further comprising a subjectadvisory device comprising the external transmission assembly, theprocessing assembly, and the user interface.
 4. The neurologicalmonitoring system of claim 3, wherein the subject advisory devicecomprises a memory for storing the data indicative of the sampledneurological signal.
 5. The neurological monitoring system of claim 1,wherein the external transmission assembly is configured to deliverpower to the implantable device via electromagnetic induction.
 6. Theneurological monitoring system of claim 5, wherein the externaltransmission assembly is configured to receive the wireless data signalfrom the implantable device via electromagnetic induction.
 7. Theneurological monitoring system of claim 5, wherein the externaltransmission assembly is configured to receive the wireless data signalfrom the implantable device via an RF link.
 8. The neurologicalmonitoring system of claim 1, wherein the external transmission assemblyis configured to receive the wireless data signal from the implantabledevice via an RF link.
 9. The neurological monitoring system of claim 1,wherein the external transmission assembly is configured tosimultaneously deliver power to the implantable device and receive thewireless data signal from the implantable device.
 10. The neurologicalmonitoring system of claim 1, wherein the wireless data signal includesa heart rate signal.
 11. The neurological monitoring system of claim 1,wherein the wireless data signal includes a respiratory signal.
 12. Theneurological monitoring system of claim 1, wherein the wireless datasignal corresponds to at least one of a blood pressure, a bloodoxygenation, a temperature, a blood flow, an ECG, an EKG, a chemicalconcentration of a neurotransmitter, a chemical concentration of amedication, and a pH in the blood.
 13. The neurological monitoringsystem of claim 1, wherein the processing assembly is adapted todetermine if the subject is in a contra-ictal condition by: extracting Nfeatures from the sampled neurological signal; generating aN-dimensional feature vector of the extracted N features for time pointsof the sampled neurological signal; and determining if the N-dimensionalfeature vector is within a contra-ictal cluster or region in theN-dimensional space.
 14. The neurological monitoring system of claim 1,wherein the neurological signal is an EEG signal.
 15. A method ofmonitoring neurological signals from a subject, said method comprising:delivering power from an external transmission assembly to an implanteddevice; sampling a neurological signal from the subject with theimplanted device; transmitting a wireless data signal from within thesubject's body to the external transmission assembly, said wireless datasignal being encoded with data indicative of the sampled neurologicalsignal; and analyzing the neurological signal from the subject using aprocessor to determine if the subject is in a contra-ictal condition,said contra-ictal condition being a neurological state in which thesubject is unlikely to transition into an ictal condition within a timeperiod.
 16. The method of claim 15, wherein the wireless data signalincludes a respiratory signal.
 17. The method of claim 15, wherein thewireless data signal corresponds to at least one of a blood pressure, ablood oxygenation, a temperature, a blood flow, an ECG, an EKG, achemical concentration of a neurotransmitter, a chemical concentrationof a medication, and a pH in the blood.
 18. The method of claim 15,wherein the wireless data signal includes a heart rate signal.
 19. Themethod of claim 15, wherein said delivering power from the externaltransmission assembly to the implanted device comprises delivering powerfrom the external transmission assembly to the implanted device viaelectromagnetic induction.
 20. The method of claim 19, wherein saidtransmitting the wireless data signal from within the subject's body tothe external transmission assembly comprises transmitting the wirelessdata signal from within the subject's body to the external transmissionassembly via electromagnetic induction.
 21. The method of claim 19,wherein said transmitting the wireless data signal from within thesubject's body to the external transmission assembly comprisestransmitting the wireless data signal from within the subject's body tothe external transmission assembly via an RF link.
 22. The method ofclaim 15, wherein said transmitting the wireless data signal from withinthe subject's body to the external transmission assembly comprisestransmitting the wireless data signal from within the subject's body tothe external transmission assembly via an RF link.
 23. The method ofclaim 15, wherein said delivering power from the external transmissionassembly is performed at the same time as said transmitting the wirelessdata signal.
 24. The method of claim 15, wherein the analyzing theneurological signal comprises: extracting N features from the sampledneurological signal; generating a N-dimensional feature vector of theextracted N features for time points of the sampled neurological signal;and determining if the N-dimensional feature vector is within acontra-ictal cluster or region in the N-dimensional space.
 25. Themethod of claim 15, wherein the neurological signal is an EEG signal.26. A neurological monitoring system comprising: an implantable device;an external transmission assembly configured to receive a wireless datasignal from the implantable device; and a processing assembly forsampling a signal from a subject, wherein the implantable deviceincludes a power assembly for receiving power from the externaltransmission assembly and a communication assembly for transmitting thewireless data signal from within a subject's body to the externaltransmission assembly, said wireless data signal being encoded with dataindicative of the sampled signal, and wherein the processing assembly isconfigured to process the wireless data signal from the implantabledevice to determine if the subject is in a contra-ictal condition, saidcontra-ictal condition being a neurological state in which the subjectis unlikely to transition into an ictal condition within a time period.27. The neurological monitoring system of claim 26, wherein the wirelessdata signal includes a heart rate signal.
 28. The neurologicalmonitoring system of claim 26, wherein the wireless data signal includesa respiratory signal.
 29. The neurological monitoring system of claim26, wherein the wireless data signal corresponds to at least one of ablood pressure, a blood oxygenation, a temperature, a blood flow, anECG, an EKG, a chemical concentration of a neurotransmitter, a chemicalconcentration of a medication, and a pH in the blood.
 30. A method ofmonitoring signals from a subject, said method comprising: deliveringpower to an implanted device; sampling a signal from the subject withthe implanted device; transmitting a wireless data signal from withinthe subject's body to an external transmission assembly, said wirelessdata signal being encoded with data indicative of the sampled signal;and analyzing the sampled signal from the subject using a processor todetermine if the subject is in a contra-ictal condition, saidcontra-ictal condition being a neurological state in which the subjectis unlikely to transition into an ictal condition within a time period.31. The method of claim 30, wherein the wireless data signal includes aheart rate signal.
 32. The method of claim 30, wherein the wireless datasignal includes a respiratory signal.
 33. The method of claim 30,wherein the wireless data signal corresponds to at least one of a bloodpressure, a blood oxygenation, a temperature, a blood flow, an ECG, anEKG, a chemical concentration of a neurotransmitter, a chemicalconcentration of a medication, and a pH in the blood.